{"id":11950,"date":"2026-02-06T08:03:27","date_gmt":"2026-02-06T07:03:27","guid":{"rendered":"https:\/\/jobwinner.ai\/resume-examples\/data-architect\/"},"modified":"2026-02-06T08:03:28","modified_gmt":"2026-02-06T07:03:28","slug":"architecte-de-donnees","status":"publish","type":"resume-examples","link":"https:\/\/jobwinner.ai\/fr\/exemples-de-cv\/architecte-de-donnees\/","title":{"rendered":"Exemples et bonnes pratiques pour la r\u00e9daction de CV d&#039;architecte de donn\u00e9es"},"content":{"rendered":"<div class=\"wrap\">\n<section id=\"example\">\n<p style=\"margin:0 0 14px; max-width:84ch;\">\n    Looking for a Data Architect resume example that&#8217;s ready for practical use? Below you&#8217;ll find three complete samples, plus an actionable guide to crafting compelling bullets, quantifying your results, and customizing your resume for a specific Data Architect opening\u2014while keeping every claim authentic.\n  <\/p>\n<h2>1. Data Architect Resume Example (Full Sample + What to Copy)<\/h2>\n<p>Most people searching for &#8220;resume example&#8221; want two essentials: a realistic sample for reference, and clear steps to tailor that sample for their own background. The following Harvard-style template is a proven standard for Data Architect roles\u2014it\u2019s clean, direct, and parses easily with most ATS systems.<\/p>\n<p>Use this as a foundation, not as a fill-in-the-blanks template. Mirror the organizational framework and depth of detail, adapting specifics to reflect your actual experience. For a faster process, you can start with the <a href=\"https:\/\/jobwinner.ai\/resume-builder\/\">resume builder<\/a> and then <a href=\"https:\/\/jobwinner.ai\/resume-tailoring\">customize your resume for each Data Architect job<\/a>.<\/p>\n<div class=\"visual quickstart-box\">\n<h3>Quick Start (5 minutes)<\/h3>\n<ol>\n<li>Choose the resume sample below that aligns best with your Data Architect focus<\/li>\n<li>Model the structure, substitute with your genuine achievements<\/li>\n<li>Sort your bullets so your highest-impact data architecture work appears first<\/li>\n<li>Run the ATS test (section 6) before applying<\/li>\n<\/ol><\/div>\n<h3>What you should copy from these examples<\/h3>\n<ul>\n<li><strong>Header with professional links<\/strong>\n<ul>\n<li>Feature LinkedIn and portfolio links that support your expertise in data architecture.<\/li>\n<li>Keep the layout direct so links remain clickable in any format.<\/li>\n<\/ul>\n<\/li>\n<li><strong>Bullets that communicate data impact<\/strong>\n<ul>\n<li>Demonstrate business value (data availability, performance, compliance, reliability, cost savings) instead of simply listing tasks.<\/li>\n<li>Reference the most relevant technologies\u2014databases, cloud platforms, ETL tools\u2014naturally within each bullet.<\/li>\n<\/ul>\n<\/li>\n<li><strong>Skills organized by area<\/strong>\n<ul>\n<li>Segment skills into Databases, Cloud, Tools, and Methodologies for easy scanning.<\/li>\n<li>Highlight core skills that directly map to the target role.<\/li>\n<\/ul>\n<\/li>\n<\/ul>\n<p>Below are three resume examples in different formats. Select the one that resembles your focus and seniority, then adjust the content to accurately reflect your own background. For more <a href=\"https:\/\/jobwinner.ai\/resume-examples\">role-specific resumes<\/a>, browse additional templates and samples.<\/p>\n<div class=\"visual resume-card\" tabindex=\"0\" aria-label=\"Data Architect resume example, classic Harvard style\">\n<div class=\"resume-base resume-classic\">\n<p class=\"name\">Jordan Miller<\/p>\n<p class=\"title\">Data Architect<\/p>\n<p class=\"contact\">\n          jordan.miller@email.com \u00b7 555-888-1234 \u00b7 Chicago, IL \u00b7 linkedin.com\/in\/jordanmiller \u00b7 portfolio.jordanmiller.com\n        <\/p>\n<div class=\"sec\">\n<p class=\"sec-title\">Professional Summary<\/p>\n<div class=\"rule\"><\/div>\n<p class=\"summary-p\">\n            Data Architect with 7+ years designing scalable data platforms and cloud-native pipelines in AWS and Azure. Experienced leading end-to-end migrations, optimizing data models for analytics, and ensuring data quality and integrity across enterprise ecosystems. Trusted partner for bridging business requirements with robust technical solutions.\n          <\/p>\n<\/p><\/div>\n<div class=\"sec\">\n<p class=\"sec-title\">Professional Experience<\/p>\n<div class=\"rule\"><\/div>\n<div class=\"row\">\n<div><strong>InsightData Corp.<\/strong>, Data Architect, Chicago, IL<\/div>\n<div class=\"right\">May 2018 to Present<\/div>\n<\/p><\/div>\n<ul class=\"bullets\">\n<li>Led architecture and deployment of a cloud data warehouse in AWS Redshift, cutting ETL processing time by 60% and supporting 4x user growth.<\/li>\n<li>Designed enterprise data models aligning 12+ source systems, reducing data redundancy and enabling unified BI dashboards.<\/li>\n<li>Implemented automated data quality checks with dbt and Airflow, decreasing monthly data issues by about 40%.<\/li>\n<li>Guided migration from on-prem SQL Server to Azure Synapse, saving $250k in annual infrastructure costs and improving SLAs.<\/li>\n<li>Collaborated with business analysts and engineers to define data governance standards, accelerating compliance certification by 4 months.<\/li>\n<\/ul>\n<div class=\"row\">\n<div><strong>UrbanBytes<\/strong>, Data Engineer, Evanston, IL<\/div>\n<div class=\"right\">Jan 2015 to Apr 2018<\/div>\n<\/p><\/div>\n<ul class=\"bullets\">\n<li>Developed ETL pipelines using Python and Talend, reducing manual data integration effort by 70%.<\/li>\n<li>Optimized data warehouse schema, improving query performance and lowering storage costs by 30%.<\/li>\n<li>Maintained data lake (S3 + Athena), improving accessibility for analytics stakeholders.<\/li>\n<li>Established data lineage mapping and improved data catalog accuracy across teams.<\/li>\n<\/ul><\/div>\n<div class=\"sec\">\n<p class=\"sec-title\">Skills<\/p>\n<div class=\"rule\"><\/div>\n<div class=\"two-col\" aria-label=\"Skills in two columns\">\n<div><strong>Databases:<\/strong> Redshift, Snowflake, SQL Server, PostgreSQL<\/div>\n<div><strong>Cloud:<\/strong> AWS (S3, Glue, Lambda), Azure Synapse<\/div>\n<div><strong>Tools:<\/strong> dbt, Airflow, Talend, Tableau<\/div>\n<div><strong>Methodologies:<\/strong> Data Modeling, ETL Automation, Data Governance<\/div>\n<\/p><\/div>\n<\/p><\/div>\n<div class=\"sec\">\n<p class=\"sec-title\">Education and Certifications<\/p>\n<div class=\"rule\"><\/div>\n<div class=\"row\">\n<div><strong>Northwestern University<\/strong>, MS Information Systems, Evanston, IL<\/div>\n<div class=\"right\">2014<\/div>\n<\/p><\/div>\n<div class=\"row\" style=\"margin-top: 6px;\">\n<div><strong>AWS Certified Solutions Architect \u2013 Associate<\/strong>, Online<\/div>\n<div class=\"right\">2021<\/div>\n<\/p><\/div>\n<div class=\"row\" style=\"margin-top: 6px;\">\n<div><strong>SAP Certified Application Associate<\/strong>, Online<\/div>\n<div class=\"right\">2019<\/div>\n<\/p><\/div>\n<\/p><\/div>\n<\/p><\/div>\n<p>      <a class=\"resume-overlay\" href=\"https:\/\/app.jobwinner.ai\/register\" target=\"_blank\" rel=\"noopener\" aria-label=\"Go to JobWinner to enhance this resume\"><br \/>\n        <span class=\"cta-btn\">Enhance my Resume<\/span><br \/>\n      <\/a>\n    <\/div>\n<p>If you want a modern, minimal approach that prioritizes ATS compatibility, check out the next example. It features a clean layout and streamlined information flow.<\/p>\n<div class=\"visual resume-card\" tabindex=\"0\" aria-label=\"Data Architect resume example, modern minimal style\">\n<div class=\"resume-base resume-modern\">\n<div class=\"top\">\n<div>\n<p class=\"name\">Priya Desai<\/p>\n<p class=\"title\">Cloud Data Architect<\/p>\n<p>            <span class=\"pill\">Data modeling \u00b7 cloud migration \u00b7 analytics enablement<\/span>\n          <\/div>\n<p class=\"contact\">\n            priya.desai@email.com<br \/>\n            555-445-7865<br \/>\n            Toronto, ON<br \/>\n            linkedin.com\/in\/priyadesai<br \/>\n            portfolio.priyadesai.com\n          <\/p>\n<\/p><\/div>\n<div class=\"sec\">\n<p class=\"sec-title\">Professional Summary<\/p>\n<div class=\"rule\"><\/div>\n<p class=\"summary-p\">\n            Experienced Cloud Data Architect specializing in designing robust, scalable architectures across AWS and GCP. Adept at leading cloud migrations, automating ELT workflows, and delivering reliable analytics platforms for global teams. Focused on optimizing data flow, reducing costs, and supporting data-driven business strategies.\n          <\/p>\n<\/p><\/div>\n<div class=\"sec\">\n<p class=\"sec-title\">Professional Experience<\/p>\n<div class=\"rule\"><\/div>\n<div class=\"row\">\n<div><strong>Maple Insights<\/strong>, Cloud Data Architect, Toronto, ON<\/div>\n<div class=\"right\">Oct 2020 to Present<\/div>\n<\/p><\/div>\n<ul class=\"bullets\">\n<li>Architected GCP data platform for global analytics, improving data delivery SLAs and integrating 10+ data sources.<\/li>\n<li>Directed migration from on-prem Hadoop to BigQuery, reducing analysis cycle times by 70%.<\/li>\n<li>Automated ELT pipelines with Cloud Composer and Dataflow, saving 20+ engineering hours each week.<\/li>\n<li>Partnered with BI and security teams to define unified data governance, accelerating audit readiness.<\/li>\n<li>Mentored four data engineers, raising platform reliability and reducing incidents.<\/li>\n<\/ul>\n<div class=\"row\">\n<div><strong>DataSpring<\/strong>, Senior Data Engineer, Toronto, ON<\/div>\n<div class=\"right\">Aug 2017 to Sep 2020<\/div>\n<\/p><\/div>\n<ul class=\"bullets\">\n<li>Developed event-driven data pipelines with Python and Kafka, increasing data freshness for analytics consumers.<\/li>\n<li>Improved data warehouse structure in Snowflake, resulting in faster query performance and lower compute costs.<\/li>\n<li>Documented data lineage and supported on-call escalations, improving transparency and reducing data errors.<\/li>\n<\/ul><\/div>\n<div class=\"sec\">\n<p class=\"sec-title\">Skills<\/p>\n<div class=\"rule\"><\/div>\n<div class=\"two-col\">\n<div><strong>Databases:<\/strong> BigQuery, Snowflake, MySQL<\/div>\n<div><strong>Cloud:<\/strong> GCP (Dataflow, Composer), AWS<\/div>\n<div><strong>Tools:<\/strong> dbt, Looker, Kafka<\/div>\n<div><strong>Methodologies:<\/strong> Data Lake Design, ELT, Security &#038; Compliance<\/div>\n<\/p><\/div>\n<\/p><\/div>\n<div class=\"sec\">\n<p class=\"sec-title\">Education and Certifications<\/p>\n<div class=\"rule\"><\/div>\n<div class=\"row\">\n<div><strong>University of Waterloo<\/strong>, BSc Computer Science, Waterloo, ON<\/div>\n<div class=\"right\">2017<\/div>\n<\/p><\/div>\n<div class=\"row\" style=\"margin-top: 6px;\">\n<div><strong>Google Cloud Professional Data Engineer<\/strong>, Online<\/div>\n<div class=\"right\">2022<\/div>\n<\/p><\/div>\n<\/p><\/div>\n<\/p><\/div>\n<p>      <a class=\"resume-overlay\" href=\"https:\/\/app.jobwinner.ai\/register\" target=\"_blank\" rel=\"noopener\" aria-label=\"Go to JobWinner to enhance this resume\"><br \/>\n        <span class=\"cta-btn\">Enhance my Resume<\/span><br \/>\n      <\/a>\n    <\/div>\n<p>If your focus is on enterprise data governance or MDM, recruiters will expect clear evidence of compliance, standardization, and large-scale enablement. The next sample foregrounds data quality and stewardship results.<\/p>\n<div class=\"visual resume-card\" tabindex=\"0\" aria-label=\"Data Architect resume example, compact technical style\">\n<div class=\"resume-base resume-compact\">\n<div class=\"header\">\n<p class=\"name\">Samuel Chen<\/p>\n<p class=\"title\">Enterprise Data Architect<\/p>\n<p class=\"contact\">\n            samuel.chen@email.com \u00b7 555-640-9876 \u00b7 New York, NY \u00b7 linkedin.com\/in\/samuelchen \u00b7 portfolio.samuelchen.com\n          <\/p>\n<\/p><\/div>\n<p class=\"tagline\">Focus: Data governance \u00b7 MDM \u00b7 regulatory compliance \u00b7 platform enablement<\/p>\n<div class=\"sec\">\n<p class=\"sec-title\">Professional Summary<\/p>\n<div class=\"rule\"><\/div>\n<p class=\"summary-p\">\n            Enterprise Data Architect with 10+ years shaping data governance, MDM, and regulatory frameworks for Fortune 500 organizations. Recognized for reducing data inconsistencies and driving audit compliance through automated controls, clear documentation, and cross-functional collaboration.\n          <\/p>\n<\/p><\/div>\n<div class=\"sec\">\n<p class=\"sec-title\">Professional Experience<\/p>\n<div class=\"rule\"><\/div>\n<div class=\"row\">\n<div><strong>Datalink Holdings<\/strong>, Enterprise Data Architect, New York, NY<\/div>\n<div class=\"right\">Jan 2016 to Present<\/div>\n<\/p><\/div>\n<ul class=\"bullets\">\n<li>Designed company-wide data governance strategy, achieving SOX and GDPR compliance across all data domains.<\/li>\n<li>Implemented MDM solution that unified 5 business units, reducing duplicate records by 65% and improving reporting accuracy.<\/li>\n<li>Built automated auditing scripts to detect data anomalies, cutting remediation times in half.<\/li>\n<li>Standardized data definitions and documentation, accelerating onboarding for analytics teams.<\/li>\n<li>Partnered with IT and compliance to lead breach simulation drills and incident response plans.<\/li>\n<\/ul>\n<div class=\"row\">\n<div><strong>Alpine Analytics<\/strong>, Data Analyst, Newark, NJ<\/div>\n<div class=\"right\">Mar 2012 to Dec 2015<\/div>\n<\/p><\/div>\n<ul class=\"bullets\">\n<li>Monitored and improved data quality metrics, increasing reliability of enterprise dashboards.<\/li>\n<li>Documented lineage for reporting pipelines, reducing support escalations.<\/li>\n<li>Supported migration to centralized data catalog, improving discoverability and reuse.<\/li>\n<\/ul><\/div>\n<div class=\"sec\">\n<p class=\"sec-title\">Skills<\/p>\n<div class=\"rule\"><\/div>\n<div class=\"two-col\">\n<div><strong>Databases:<\/strong> Oracle, SQL Server, SAP HANA<\/div>\n<div><strong>Cloud:<\/strong> Azure, AWS<\/div>\n<div><strong>Tools:<\/strong> Informatica MDM, Collibra, Power BI<\/div>\n<div><strong>Methodologies:<\/strong> Data Governance, Regulatory Compliance, Data Quality Management<\/div>\n<\/p><\/div>\n<\/p><\/div>\n<div class=\"sec\">\n<p class=\"sec-title\">Education and Certifications<\/p>\n<div class=\"rule\"><\/div>\n<div class=\"row\">\n<div><strong>Columbia University<\/strong>, MS Data Science, New York, NY<\/div>\n<div class=\"right\">2011<\/div>\n<\/p><\/div>\n<div class=\"row\" style=\"margin-top: 6px;\">\n<div><strong>Certified Data Management Professional (CDMP)<\/strong>, Online<\/div>\n<div class=\"right\">2020<\/div>\n<\/p><\/div>\n<\/p><\/div>\n<\/p><\/div>\n<p>      <a class=\"resume-overlay\" href=\"https:\/\/app.jobwinner.ai\/register\" target=\"_blank\" rel=\"noopener\" aria-label=\"Go to JobWinner to enhance this resume\"><br \/>\n        <span class=\"cta-btn\">Enhance my Resume<\/span><br \/>\n      <\/a>\n    <\/div>\n<p>Across all three, you\u2019ll see a consistent emphasis on specific expertise, quantifiable impact, logical grouping of skills, and links to supporting materials. Formatting may differ, but the narrative style\u2014evidence first\u2014remains constant.<\/p>\n<p class=\"note\">Tip: If your portfolio is limited, highlight two relevant architecture diagrams or technical write-ups with clear context and results.<\/p>\n<h3>Role variations (pick the closest version to your target job)<\/h3>\n<p>Many &#8220;Data Architect&#8221; jobs have widely different responsibilities. Select the closest focus and echo its language and bullet structure using your actual work history.<\/p>\n<h3>Cloud Data Platform variation<\/h3>\n<p><strong>Keywords to include:<\/strong> Cloud migration, Redshift, BigQuery, Data pipelines<\/p>\n<ul>\n<li><strong>Bullet pattern 1:<\/strong> Architected <em>cloud-based data warehouse<\/em> on [platform], reducing ETL times by [metric] and supporting [business result].<\/li>\n<li><strong>Bullet pattern 2:<\/strong> Automated <em>data ingestion<\/em> using [tool], improving data freshness and reliability for [user group].<\/li>\n<\/ul>\n<h3>Data Governance \/ MDM variation<\/h3>\n<p><strong>Keywords to include:<\/strong> Data governance, MDM, compliance, data quality<\/p>\n<ul>\n<li><strong>Bullet pattern 1:<\/strong> Established enterprise <em>data governance framework<\/em>, achieving [compliance] and reducing [errors\/duplication] by [metric].<\/li>\n<li><strong>Bullet pattern 2:<\/strong> Implemented <em>MDM solution<\/em> across [business units], increasing data accuracy and reporting consistency.<\/li>\n<\/ul>\n<h3>Analytics Enablement variation<\/h3>\n<p><strong>Keywords to include:<\/strong> Data modeling, BI tools, ELT, stakeholder collaboration<\/p>\n<ul>\n<li><strong>Bullet pattern 1:<\/strong> Designed <em>data model<\/em> supporting [analytical workload], improving dashboard performance and reducing ad-hoc queries by [metric].<\/li>\n<li><strong>Bullet pattern 2:<\/strong> Partnered with analysts to streamline <em>data delivery<\/em>, decreasing time-to-insight by [amount].<\/li>\n<\/ul>\n<\/section>\n<section id=\"recruiter-scan\">\n<h2>2. What recruiters scan first<\/h2>\n<p>Recruiters typically skim, not read, on their initial review. They\u2019re searching for clear signs of job match and measurable data platform impact. Use this checklist as a self-audit before you submit.<\/p>\n<ul>\n<li><strong>Role match in the top section:<\/strong> Title, summary, and skills closely mirror the job\u2019s technology stack and primary responsibilities.<\/li>\n<li><strong>Most relevant impact up front:<\/strong> First bullets for each experience highlight results that map to the target posting.<\/li>\n<li><strong>Concrete outcomes:<\/strong> At least one quantifiable metric per position (data latency, cost, compliance, user enablement, reliability).<\/li>\n<li><strong>Portfolio or project links:<\/strong> LinkedIn or portfolio links placed prominently, demonstrating credibility.<\/li>\n<li><strong>Readable formatting:<\/strong> Reliable sectioning, consistent dates, and layouts that won\u2019t confuse ATS parsing.<\/li>\n<\/ul>\n<p class=\"note\">If you only optimize one thing, ensure your opening bullets are both impactful and directly relevant for data architecture roles.<\/p>\n<\/section>\n<section id=\"structure\">\n<h2>3. How to Structure a Data Architect Resume Section by Section<\/h2>\n<p>Structure is pivotal\u2014hiring teams glance for fit and relevance before diving into depth. The best Data Architect resumes make your expertise, technical stack, and most persuasive results instantly apparent in section one.<\/p>\n<p>Think less about covering everything\u2014focus on surfacing the right details in the right order. Your resume acts as a roadmap: the bullets frame your capabilities, your portfolio or documentation supports your claims.<\/p>\n<h3>Recommended section order (with what to include)<\/h3>\n<ul>\n<li><strong>Header<\/strong>\n<ul>\n<li>Name, intended title (Data Architect), email, mobile, city &#038; country.<\/li>\n<li>Links: LinkedIn, portfolio, technical write-ups\u2014only what demonstrates relevant expertise.<\/li>\n<li>Physical address is unnecessary.<\/li>\n<\/ul>\n<\/li>\n<li><strong>Summary (optional)<\/strong>\n<ul>\n<li>Best when clarifying your focus: cloud, governance\/MDM, analytics, or hybrid.<\/li>\n<li>2-4 lines covering: specialty, core platforms, and at least one business outcome or technical result.<\/li>\n<li>Use the <a href=\"https:\/\/jobwinner.ai\/resume-tailoring\/professional-summary-generator\/\">summary generator<\/a> to draft a sharper profile, then fine-tune for accuracy.<\/li>\n<\/ul>\n<\/li>\n<li><strong>Professional Experience<\/strong>\n<ul>\n<li>List positions in reverse order, detailing dates and locations.<\/li>\n<li>Include 3-5 accomplishment-based bullets per job, most relevant first.<\/li>\n<\/ul>\n<\/li>\n<li><strong>Skills<\/strong>\n<ul>\n<li>Categorize: Databases, Cloud, Tools, Methodologies.<\/li>\n<li>Prioritize skills matching the job\u2019s requirements, removing outdated or unrelated ones.<\/li>\n<li>Not sure which skills matter most for your ideal job? Leverage the <a href=\"https:\/\/jobwinner.ai\/skills-insights\/\">skills insights<\/a> analyzer for real-time trends.<\/li>\n<\/ul>\n<\/li>\n<li><strong>Education and Certifications<\/strong>\n<ul>\n<li>Include city and country for degrees when applicable.<\/li>\n<li>For certifications, use \u201cOnline\u201d if no physical site applies.<\/li>\n<\/ul>\n<\/li>\n<\/ul>\n<\/section>\n<section id=\"bullets\">\n<h2>4. Data Architect Bullet Points and Metrics Playbook<\/h2>\n<p>Effective bullets serve triple duty: highlighting delivery results, technical improvement, and integrating the language hiring managers expect. Upgrading your bullet points is the quickest way to boost your resume\u2019s traction.<\/p>\n<p>If your bullets largely describe job functions (\u201cresponsible for data models&#8230;\u201d), you\u2019re missing a chance to present value. Replace them with evidence\u2014delivered projects, cost or performance improvements, successful migrations, increased data quality, or measurable business outcomes.<\/p>\n<h3>A reusable bullet formula for Data Architect roles<\/h3>\n<ul>\n<li><strong>Action + Scope + Stack + Outcome<\/strong>\n<ul>\n<li><strong>Action:<\/strong> architected, migrated, standardized, automated, unified, optimized<\/li>\n<li><strong>Scope:<\/strong> platform, warehouse, pipeline, governance framework, MDM rollout<\/li>\n<li><strong>Stack:<\/strong> specific tools or clouds (Redshift, Snowflake, dbt, Azure, GCP, Informatica)<\/li>\n<li><strong>Outcome:<\/strong> reduced cost, improved compliance, decreased downtime, faster analytics, higher adoption<\/li>\n<\/ul>\n<\/li>\n<\/ul>\n<h3>Where to quickly find relevant metrics (by Data Architect focus)<\/h3>\n<ul>\n<li><strong>Performance:<\/strong> Query speed, ETL\/ELT runtimes, data refresh lag, uptime percentage<\/li>\n<li><strong>Cost:<\/strong> Infrastructure savings, compute\/storage reduction, licensing costs cut<\/li>\n<li><strong>Quality &#038; Reliability:<\/strong> Data accuracy rate, error frequency, failed jobs reduced, data issue incidents<\/li>\n<li><strong>Compliance:<\/strong> Time to compliance, audits passed, regulatory milestones met, data breaches prevented<\/li>\n<li><strong>User Enablement:<\/strong> Users onboarded, new dashboards enabled, data source integrations, ad-hoc queries reduced<\/li>\n<\/ul>\n<p><strong>Fast sources for these numbers:<\/strong><\/p>\n<ul>\n<li>Monitoring tools (CloudWatch, DataDog, native cloud dashboards)<\/li>\n<li>Logs and pipeline reports (Airflow, dbt, custom scripts)<\/li>\n<li>Finance\/infra spend dashboards, audit logs, and usage reports<\/li>\n<li>BI usage stats (Looker\/Tableau dashboards)<\/li>\n<\/ul>\n<p>Looking for additional wording ideas? Check out these <a href=\"https:\/\/jobwinner.ai\/resume-tailoring\/responsabilities-bullet-points\/\">responsibility bullet samples<\/a> and adapt the structure using your actual accomplishments.<\/p>\n<p>Here\u2019s a before\/after table to model powerful Data Architect bullet rewrites.<\/p>\n<div class=\"visual tablewrap\" role=\"img\" aria-label=\"Before and after bullet point examples for Data Architect resume\">\n<table>\n<thead>\n<tr>\n<th><span class=\"bad\">Before<\/span> (weak)<\/th>\n<th><span class=\"good\">After<\/span> (strong)<\/th>\n<\/tr>\n<\/thead>\n<tbody>\n<tr>\n<td>Maintained the company\u2019s data warehouse environment.<\/td>\n<td>Redesigned Snowflake schema and automated daily ETL, reducing query times by 45% and cutting storage costs by $100k annually.<\/td>\n<\/tr>\n<tr>\n<td>Helped with data migration projects.<\/td>\n<td>Led migration from on-premise SQL Server to AWS Redshift, enabling real-time analytics and saving 30% on infrastructure spend.<\/td>\n<\/tr>\n<tr>\n<td>Was responsible for data governance processes.<\/td>\n<td>Established governance framework and implemented Collibra, improving data lineage accuracy and supporting GDPR certification ahead of deadline.<\/td>\n<\/tr>\n<\/tbody>\n<\/table><\/div>\n<h3>Typical weak patterns (and how to turn them around)<\/h3>\n<p><strong>&#8220;Responsible for databases&#8230;&#8221;<\/strong> \u2192 Show what you built or improved<\/p>\n<ul>\n<li>Weak: &#8220;Responsible for databases and data pipelines&#8221;<\/li>\n<li>Strong: &#8220;Unified and automated five data pipelines, increasing data reliability and reducing downtime by 60%&#8221;<\/li>\n<\/ul>\n<p><strong>&#8220;Worked with analysts to&#8230;&#8221;<\/strong> \u2192 Clarify your personal impact<\/p>\n<ul>\n<li>Weak: &#8220;Worked with analysts to provide data access&#8221;<\/li>\n<li>Strong: &#8220;Partnered with analytics team to design self-service data models, decreasing ad-hoc queries by 40%&#8221;<\/li>\n<\/ul>\n<p><strong>&#8220;Helped with migration&#8230;&#8221;<\/strong> \u2192 Specify your ownership and scale<\/p>\n<ul>\n<li>Weak: &#8220;Helped with migration to the cloud&#8221;<\/li>\n<li>Strong: &#8220;Architected and executed migration of 12TB data warehouse to GCP BigQuery, eliminating legacy maintenance costs&#8221;<\/li>\n<\/ul>\n<p class=\"note\">If you don\u2019t have exact metrics, provide reasonable estimates you can back up. For example: &#8220;about 40%&#8221; or &#8220;reduced incidents by half.&#8221;<\/p>\n<\/section>\n<section id=\"tailor\">\n<h2>5. Tailor Your Data Architect Resume to a Job Description (Step by Step + Prompt)<\/h2>\n<p>Customizing your resume for each opportunity is crucial. Tailoring isn\u2019t about embellishment; it\u2019s about framing your achievements with the language and focus the employer cares about most.<\/p>\n<p>Want a streamlined path? <a href=\"https:\/\/jobwinner.ai\/resume-tailoring\">Use JobWinner AI tailoring<\/a>, then review the results for 100% factual accuracy. For summary rewrites, the <a href=\"https:\/\/jobwinner.ai\/resume-tailoring\/professional-summary-generator\/\">summary generator<\/a> can help you sharpen your message.<\/p>\n<h3>5 steps to customize honestly<\/h3>\n<ol>\n<li><strong>Extract core keywords<\/strong>\n<ul>\n<li>Capture cloud platforms, critical database types, governance, integrations, and migration keywords.<\/li>\n<li>Highlight those terms repeated throughout the job ad\u2014they show what\u2019s top of mind for the employer.<\/li>\n<\/ul>\n<\/li>\n<li><strong>Map keywords to true experience<\/strong>\n<ul>\n<li>For every keyword, identify a bullet, project, or result where you delivered real value.<\/li>\n<li>If you lack depth in one area, emphasize adjacent strengths or relevant work.<\/li>\n<\/ul>\n<\/li>\n<li><strong>Revise the top third<\/strong>\n<ul>\n<li>Update your title, summary, and skills order to reflect the job\u2019s focus (cloud, MDM, analytics, etc.).<\/li>\n<li>Move the most in-demand skills up top.<\/li>\n<\/ul>\n<\/li>\n<li><strong>Reorder bullets by relevance<\/strong>\n<ul>\n<li>Place your most applicable bullet points first for each job entry.<\/li>\n<li>Trim bullets that don\u2019t directly support the target role.<\/li>\n<\/ul>\n<\/li>\n<li><strong>Double-check for credibility<\/strong>\n<ul>\n<li>Every statement should be easy to explain if asked for details or context.<\/li>\n<li>If you\u2019re not confident you can defend it, reword or remove.<\/li>\n<\/ul>\n<\/li>\n<\/ol>\n<h3>Tailoring pitfalls to avoid<\/h3>\n<ul>\n<li>Copying job description wording exactly<\/li>\n<li>Claiming proficiency in every single tool listed<\/li>\n<li>Including skills you haven\u2019t used in recent roles<\/li>\n<li>Altering job titles beyond what\u2019s accurate<\/li>\n<li>Inflating metrics or project scale<\/li>\n<\/ul>\n<p>True tailoring means choosing your most relevant, defendable evidence, not stretching your resume to fit every keyword.<\/p>\n<p>Need a tailored draft you can edit? Use this prompt for a data architecture role\u2014remember to paste your own content and the job description.<\/p>\n<div class=\"visual prompt-box\" aria-label=\"Copy and paste resume tailoring prompt\">\n<div class=\"prompt-head\">\n        <button class=\"prompt-copy-btn\" type=\"button\" onclick=\"jwCopySection('tailor-prompt', this)\">Copy prompt<\/button>\n      <\/div>\n<pre><code id=\"tailor-prompt\">Task: Tailor my Data Architect resume to the job description below without inventing experience.\n\nRules:\n- Keep everything truthful and consistent with my original resume.\n- Prefer strong action verbs and measurable impact.\n- Use relevant keywords from the job description naturally (no keyword stuffing).\n- Keep formatting ATS-friendly (simple headings, plain text).\n\nInputs:\n1) My current resume:\n&lt;RESUME&gt;\n[Paste your resume here]\n&lt;\/RESUME&gt;\n\n2) Job description:\n&lt;JOB_DESCRIPTION&gt;\n[Paste the job description here]\n&lt;\/JOB_DESCRIPTION&gt;\n\nOutput:\n- A tailored resume (same structure as my original)\n- 8 to 12 improved bullets, prioritizing the most relevant achievements\n- A refreshed Skills section grouped by: Databases, Cloud, Tools, Methodologies\n- A short list of keywords you used (for accuracy checking)<\/code><\/pre>\n<\/p><\/div>\n<p class=\"note\">If the job focuses on data governance or security, be sure to include a bullet about compliance frameworks or access controls\u2014only if it accurately reflects your work.<\/p>\n<\/section>\n<section id=\"ats\">\n<h2>6. Data Architect Resume ATS Best Practices<\/h2>\n<p>When it comes to ATS, simplicity and clarity win. The strongest Data Architect resumes use a single-column format, standard section headers, uniform date formatting, and plain-text skills\u2014no graphics or sidebars that can disrupt parsing.<\/p>\n<p>Think of it like this: predictable formatting helps ATS reliably extract your skills, dates, and job titles, which means your profile won\u2019t be disqualified by the system before a human sees it. Always review your resume with an <a href=\"https:\/\/jobwinner.ai\/ats-resume-checker\/\">ATS resume checker<\/a> to catch common problems early.<\/p>\n<h3>Make your resume both ATS and human-friendly<\/h3>\n<ul>\n<li><strong>Standardized headings<\/strong>\n<ul>\n<li>Professional Experience, Skills, Education, etc. Stick to universally recognized labels.<\/li>\n<li>Skip creative headings that could confuse the parser.<\/li>\n<\/ul>\n<\/li>\n<li><strong>Consistent structure<\/strong>\n<ul>\n<li>Uniform date formatting and clear section breaks.<\/li>\n<li>Keep important details in the main column\u2014avoid dense sidebars for key content.<\/li>\n<\/ul>\n<\/li>\n<li><strong>Portfolio links in the header<\/strong>\n<ul>\n<li>Place LinkedIn\/portfolio at the top for easy access\u2014don\u2019t hide them in footers or graphics.<\/li>\n<li>Avoid embedding links in images.<\/li>\n<\/ul>\n<\/li>\n<li><strong>Plain-text skills only<\/strong>\n<ul>\n<li>No skill graphs, progress bars, or visual charts.<\/li>\n<li>Group your core skills for easy skimming by recruiter and machine alike.<\/li>\n<\/ul>\n<\/li>\n<\/ul>\n<p>Here\u2019s an ATS do\/avoid table to help you safeguard your resume\u2019s parsing and ranking.<\/p>\n<div class=\"visual tablewrap\" role=\"img\" aria-label=\"ATS do and avoid checklist for Data Architect resumes\">\n<table>\n<thead>\n<tr>\n<th>Do (ATS friendly)<\/th>\n<th>Avoid (common parsing issues)<\/th>\n<\/tr>\n<\/thead>\n<tbody>\n<tr>\n<td>Standard headings, even spacing, clear format<\/td>\n<td>Icons for sections, text inside images, unusual layouts<\/td>\n<\/tr>\n<tr>\n<td>Skills in grouped, plain text<\/td>\n<td>Skill bars, visual ratings, pie charts<\/td>\n<\/tr>\n<tr>\n<td>Bullets with concise, impact-driven details<\/td>\n<td>Wall-of-text paragraphs that hide keywords and results<\/td>\n<\/tr>\n<tr>\n<td>PDF version unless otherwise requested<\/td>\n<td>Scanned PDFs, images, or rare file types<\/td>\n<\/tr>\n<\/tbody>\n<\/table><\/div>\n<h3>How to quickly check your own ATS compatibility<\/h3>\n<ol>\n<li>Export your resume as a PDF<\/li>\n<li>Open it in Google Docs or another PDF reader<\/li>\n<li>Highlight and copy all text<\/li>\n<li>Paste into a plain text editor<\/li>\n<\/ol>\n<p>If text is jumbled, section headers are missing, or skill lists are broken, revise until it copies over cleanly\u2014otherwise, an ATS might miss your key qualifications.<\/p>\n<p class=\"note\">Final check: Always paste your resume into a text editor before sending. If the result isn\u2019t clean, fix before you submit.<\/p>\n<\/section>\n<section id=\"optimize\">\n<h2>7. Data Architect Resume Optimization Tips<\/h2>\n<p>Optimization is your last review before applying. The objective is to maximize clarity, highlight your strongest fit, and eliminate weak or redundant details.<\/p>\n<p>Work in layers: first, the header\/summary\/skills for relevance; then, bullet points for impact; finally, overall consistency and formatting. Repeat this process for each role you apply to, not just once for your whole search.<\/p>\n<h3>High-return tweaks for Data Architect resumes<\/h3>\n<ul>\n<li><strong>Make top section alignment instant<\/strong>\n<ul>\n<li>Update your target title, summary, and skills to match the main requirements in the job ad.<\/li>\n<li>Move the key platforms\/tools up in your skill sections.<\/li>\n<li>Reorder bullets to feature the most role-relevant achievements first.<\/li>\n<\/ul>\n<\/li>\n<li><strong>Sharpen bullet credibility<\/strong>\n<ul>\n<li>Swap generic bullets for specific outcomes, technologies, and scale.<\/li>\n<li>Quantify at least one result per job (cost, speed, quality, compliance, user impact).<\/li>\n<li>Remove overlap or vague claims\u2014each bullet should add unique evidence.<\/li>\n<\/ul>\n<\/li>\n<li><strong>Showcase verifyable proof<\/strong>\n<ul>\n<li>Link to one or two real-world architecture diagrams or write-ups in your portfolio.<\/li>\n<li>Highlight completed migrations, compliance certifications, or platform launches.<\/li>\n<\/ul>\n<\/li>\n<\/ul>\n<h3>Avoid these resume-killing mistakes<\/h3>\n<ul>\n<li><strong>Burying major achievements:<\/strong> Placing your most impactful project in a low-visibility bullet<\/li>\n<li><strong>Inconsistent formatting:<\/strong> Switching between different date formats or tense<\/li>\n<li><strong>Repeating the same point:<\/strong> Duplicating bullets that describe nearly identical work<\/li>\n<li><strong>Starting with duties:<\/strong> Opening each job with &#8220;responsible for&#8221; instead of impact\/results<\/li>\n<li><strong>Cluttered skills lists:<\/strong> Listing outdated or unrelated tools (e.g., \u201cMS Office\u201d or \u201cEmail\u201d)<\/li>\n<\/ul>\n<h3>Resume anti-patterns that immediately reduce your chances<\/h3>\n<ul>\n<li><strong>Generic intro lines:<\/strong> &#8220;Dynamic professional with strong communication skills&#8221;<\/li>\n<li><strong>Unclear scope\/ownership:<\/strong> &#8220;Worked on data systems&#8221; (But which? What was your part?)<\/li>\n<li><strong>Skills overload:<\/strong> 30+ tools with no organization or context<\/li>\n<li><strong>Responsibilities disguised as results:<\/strong> &#8220;In charge of data quality&#8221; (What did you actually achieve?)<\/li>\n<li><strong>Unverifiable claims:<\/strong> &#8220;World-class architect,&#8221; &#8220;Pioneered industry-changing solution&#8221;<\/li>\n<\/ul>\n<h3>Rapid self-review scorecard<\/h3>\n<p>Use this table for a focused, two-minute check. If you can improve just one dimension, start with relevance and concrete results. To create a customized version quickly, <a href=\"https:\/\/jobwinner.ai\/resume-tailoring\">try JobWinner AI tailoring<\/a> and then refine as needed.<\/p>\n<div class=\"visual tablewrap\" role=\"img\" aria-label=\"Data Architect resume optimization scorecard\">\n<table>\n<thead>\n<tr>\n<th>Area<\/th>\n<th>What strong looks like<\/th>\n<th>Quick fix<\/th>\n<\/tr>\n<\/thead>\n<tbody>\n<tr>\n<td>Relevance<\/td>\n<td>Header, summary, and skills align with job focus<\/td>\n<td>Adjust summary and reorder skills for each application<\/td>\n<\/tr>\n<tr>\n<td>Impact<\/td>\n<td>Bullets show measurable improvements<\/td>\n<td>Quantify at least one outcome per position<\/td>\n<\/tr>\n<tr>\n<td>Proof<\/td>\n<td>Portfolio or project links support claims<\/td>\n<td>Link technical write-ups, diagrams, or real deployments<\/td>\n<\/tr>\n<tr>\n<td>Clarity<\/td>\n<td>Consistent structure and readable formatting<\/td>\n<td>Reduce wordiness and standardize sections<\/td>\n<\/tr>\n<tr>\n<td>Credibility<\/td>\n<td>Specific, defensible statements without exaggeration<\/td>\n<td>Replace vague claims with well-scoped, tool-backed results<\/td>\n<\/tr>\n<\/tbody>\n<\/table><\/div>\n<p class=\"note\"><strong>Final tip:<\/strong> Read your resume aloud. Any bullet you can\u2019t defend with a real story, rephrase or delete.<\/p>\n<\/section>\n<section id=\"beyond\">\n<h2>8. What to Prepare Beyond Your Resume<\/h2>\n<p>Your resume earns you an interview\u2014but every line on it should point to a story or technical artifact you can expand on. Treat your resume as an annotated outline, with deeper specifics ready as backup. Before you start conversations, use <a href=\"https:\/\/jobwinner.ai\/interview-preparation\/\">interview prep tools<\/a> to practice discussing your design decisions, migrations, or compliance achievements.<\/p>\n<h3>Be ready to elaborate on every point<\/h3>\n<ul>\n<li><strong>For each bullet:<\/strong> Provide context, describe your approach, share tradeoffs you considered, and clarify your measurement methods.<\/li>\n<li><strong>For metrics:<\/strong> Explain your baseline, how you measured impact, and any assumptions made.<\/li>\n<li><strong>For tools\/platforms:<\/strong> Be prepared for deep dives (e.g., specifics of your AWS, GCP, or dbt usage).<\/li>\n<li><strong>For projects:<\/strong> Tell the &#8220;why,&#8221; your unique contribution, lessons learned, and retrospective improvements.<\/li>\n<\/ul>\n<h3>Prepare your supporting evidence<\/h3>\n<ul>\n<li>Update your portfolio: add diagrams, sample data models, or write-ups that show your thought process.<\/li>\n<li>Keep architecture sketches or compliance documentation ready for technical interviews.<\/li>\n<li>Have sanitized code samples or scripts (no confidential info) that highlight your work.<\/li>\n<li>Rehearse one or two major projects, focusing on your logic and the business impact.<\/li>\n<\/ul>\n<p class=\"note\">The best interviews come when your resume sparks curiosity and you\u2019re immediately ready with credible, detailed answers.<\/p>\n<\/section>\n<section id=\"checklist\">\n<h2>9. Final Pre-Submission Checklist<\/h2>\n<p>Run through this 60-second check before you hit submit:<\/p>\n<div class=\"visual checklist-box\">\n      <label><br \/>\n        <input type=\"checkbox\"> Top section (header + summary + skills) reflects the job\u2019s tools and focus<br \/>\n      <\/label><br \/>\n      <label><br \/>\n        <input type=\"checkbox\"> First bullet for each job is the most relevant, impressive achievement<br \/>\n      <\/label><br \/>\n      <label><br \/>\n        <input type=\"checkbox\"> At least 3-5 bullets include quantifiable outcomes or business value<br \/>\n      <\/label><br \/>\n      <label><br \/>\n        <input type=\"checkbox\"> Portfolio or LinkedIn links are correct and display recent, relevant projects<br \/>\n      <\/label><br \/>\n      <label><br \/>\n        <input type=\"checkbox\"> Passed the ATS text copy-paste test successfully<br \/>\n      <\/label><br \/>\n      <label><br \/>\n        <input type=\"checkbox\"> No spelling mistakes, consistent tense and date formatting<br \/>\n      <\/label><br \/>\n      <label><br \/>\n        <input type=\"checkbox\"> File is named professionally (FirstName_LastName_Resume.pdf)<br \/>\n      <\/label><br \/>\n      <label><br \/>\n        <input type=\"checkbox\"> Can confidently discuss every bullet and claim in detail during interviews<br \/>\n      <\/label>\n    <\/div>\n<\/section>\n<section id=\"faqs\">\n<h2>10. Data Architect Resume FAQs<\/h2>\n<p>Double-check these common Data Architect resume questions before submitting. The right answer is sometimes subtle, but getting these details right separates strong resumes from average ones.<\/p>\n<div class=\"visual\" role=\"img\" aria-label=\"Data Architect resume FAQs accordion\">\n<div style=\"padding: 14px;\">\n<details>\n<summary>How long should my Data Architect resume be?<\/summary>\n<p>\n            For most Data Architect roles, a single page works if you have less than 8\u201310 years of experience. Go to two pages only if you have extensive leadership, major platform builds, or significant compliance projects\u2014always prioritize the most relevant details on page one. Trim early or repetitive bullets.\n          <\/p>\n<\/details>\n<details>\n<summary>Should I include a summary?<\/summary>\n<p>\n            Including a summary is optional, but it\u2019s valuable if it clarifies your data architecture focus\u2014cloud migration, governance, analytics enablement, etc. Keep it concise (2\u20134 lines), mention your key platforms\/tools, and highlight a business or technical outcome. Skip generic statements and instead use language specific to your specialization.\n          <\/p>\n<\/details>\n<details>\n<summary>How many bullet points per job is best?<\/summary>\n<p>\n            Three to five well-crafted bullets per position are ideal\u2014this keeps your resume readable and ensures each bullet adds new value. If you have more, combine or cut repetitive points. Make sure your top bullet is the strongest and most relevant for data architecture.\n          <\/p>\n<\/details>\n<details>\n<summary>Do I need portfolio or GitHub links?<\/summary>\n<p>\n            While not always mandatory, links to a portfolio, GitHub, or technical write-ups provide evidence of your architectural thinking and project history. If your code is private, showcase architecture diagrams, workflows, or anonymized descriptions of your most impactful data projects.\n          <\/p>\n<\/details>\n<details>\n<summary>What if I don&#8217;t have hard metrics?<\/summary>\n<p>\n            Use directional or operational metrics you can explain: data processing times improved, cost reductions, error rates dropped, or increased adoption. If precise numbers aren\u2019t available, describe the scale (e.g., &#8220;managed data lake serving 50+ users&#8221;) and be ready to provide context in interviews.\n          <\/p>\n<\/details>\n<details>\n<summary>Is listing many tools\/technologies a negative?<\/summary>\n<p>\n            Listing too many tools can dilute your core focus and reduce clarity for both ATS and recruiters. Instead, group and prioritize the most relevant platforms\u2014especially those emphasized in the job posting. Leave off outdated, infrequently used, or unrelated technologies.\n          <\/p>\n<\/details>\n<details>\n<summary>Should contract or consultant work be included?<\/summary>\n<p>\n            Absolutely\u2014if relevant. Format contract or freelance engagements like standard employment entries, specifying the client type (e.g., \u201cFreelance Data Architect, Various Healthcare Clients\u201d), and highlight the results you delivered. For multiple short contracts, group them and focus on the most significant outcomes.\n          <\/p>\n<\/details>\n<details>\n<summary>How do I show impact early in my career?<\/summary>\n<p>\n            Emphasize incremental improvements and clear ownership, even if small in scope. For example, &#8220;Automated ETL tasks saving 10+ hours per month&#8221; or &#8220;Improved data quality checks, reducing validation issues by half.&#8221; Mention mentorships, cross-team contributions, and your part in successful migrations or upgrades.\n          <\/p>\n<\/details>\n<details>\n<summary>How should I handle NDA restrictions in my experience?<\/summary>\n<p>\n            Describe your work in general, non-proprietary terms: &#8220;Designed architecture supporting high-availability analytics for Fortune 500 client,&#8221; rather than &#8220;for [CompanyName].&#8221; Focus on the scale, the technologies, and your approach\u2014avoid confidential specifics. In interviews, be transparent about what you can and cannot share.\n          <\/p>\n<\/details><\/div>\n<\/p><\/div>\n<p class=\"note\">\n      Looking for a polished, ATS-ready template before customization? Browse <a href=\"https:\/\/jobwinner.ai\/resume-templates\/\">resume layouts<\/a> designed for Data roles.\n    <\/p>\n<\/section>\n<\/div>\n","protected":false},"excerpt":{"rendered":"<p>D\u00e9couvrez comment cr\u00e9er un CV d&#039;architecte de donn\u00e9es exceptionnel gr\u00e2ce \u00e0 des exemples concrets, aux meilleures pratiques des syst\u00e8mes de suivi des candidatures (ATS) et aux conseils d&#039;experts pour adapter votre candidature et d\u00e9crocher votre prochain poste ax\u00e9 sur les donn\u00e9es.<\/p>","protected":false},"author":3,"featured_media":0,"parent":0,"template":"","type-resume-example":[101],"class_list":["post-11950","resume-examples","type-resume-examples","status-publish","hentry","type-resume-example-data-analytics"],"jetpack_sharing_enabled":true,"_links":{"self":[{"href":"https:\/\/jobwinner.ai\/fr\/wp-json\/wp\/v2\/resume-examples\/11950","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/jobwinner.ai\/fr\/wp-json\/wp\/v2\/resume-examples"}],"about":[{"href":"https:\/\/jobwinner.ai\/fr\/wp-json\/wp\/v2\/types\/resume-examples"}],"author":[{"embeddable":true,"href":"https:\/\/jobwinner.ai\/fr\/wp-json\/wp\/v2\/users\/3"}],"wp:attachment":[{"href":"https:\/\/jobwinner.ai\/fr\/wp-json\/wp\/v2\/media?parent=11950"}],"wp:term":[{"taxonomy":"type-resume-example","embeddable":true,"href":"https:\/\/jobwinner.ai\/fr\/wp-json\/wp\/v2\/type-resume-example?post=11950"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}