Capital One
Principal Data Analyst - Strategy and Analytics
$143K–$164K
New York, NY · Principal · Full-time · Posted Oct 20, 2026
- Experience
- Bachelor’s degree route: at least 5 years performing data analytics; Master’s degree route: at least 3 years. Also at least 3 years in each of scripting, BI visualization, and querying/analyzing data; preferred experience includes 4 years coding and other stated 2- or 4-year qualifications.
- Education
- Bachelor’s degree in a quantitative field, or Master’s degree; required degree must be obtained on or before the scheduled start date.
- Visa sponsorship
- Capital One will consider sponsoring a new qualified applicant for employment authorization.
About the job
Owns analytics engineering and data strategy, building governed, high-quality data models and self-service analytics that help teams find trusted metrics and make decisions.
What you'll do
- Design and manage data transformation layers, cubes, warehouses, models, and the analytics engineering roadmap.
- Improve data quality, governance, metadata, observability, dashboards, and self-service; support legacy-platform modernization and migration.
- Analyze data, validate models, collaborate with business teams, and review and optimize code and analytics, including AI-generated work.
What they ask for
- Bachelor’s degree in a quantitative field plus at least 5 years of data analytics experience, or a Master’s degree plus at least 3 years; required degree must be obtained by the scheduled start date.
- At least 3 years working with a scripting language.
- At least 3 years using a business intelligence visualization tool.
- At least 3 years querying, analyzing, and working with data languages and platforms.
Nice to have
- Master’s degree in a STEM discipline.
- At least 4 years coding in Python, R, Spark, or SQL; process improvement, AWS, and financial-services data governance experience are also preferred.
Pay
$143,200 - $163,500 USD base salary (New York, NY; annual).
Tools
SQL, Python, R, Spark, AWS, Agile, Lean, Six Sigma
AI focus
Build a semantic layer and AI interfaces that support data discovery; work with AI tools and review, refine, and iterate on AI-generated code and analyses.
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