Senior Data Analyst
@ Capital One

McLean, VA
$109,000
On Site
Full Time
Posted 23 hours ago

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Job Details

About the Role

At Capital One, data is at the center of everything we do. As a Senior Data Analyst, you will leverage analytic and technical skills to innovate, build, and maintain well-managed data solutions and capabilities to tackle business problems.

Core Responsibilities

This role involves three main types of work:

  • Innovation: Use open source and digital technologies to mine complex and varied data sources and build self-service data solutions.
  • Business Intelligence: Partner with business units to translate needs, develop metrics, dashboards, and provide insights through data visualization.
  • Data Management: Ensure data quality management with metadata, lineage, and governance while collaborating with tech teams on security and access controls.

Qualifications

Basic Qualifications: Bachelor's degree in a quantitative field or progress toward a Master’s, with at least 2 years of experience in data analytics, proficiency in one scripting language, experience with BI visualization tools, and data querying.

Preferred Qualifications: Master’s degree, advanced coding (Python, R, Spark, SQL), AWS experience, knowledge of data governance and quality management, and familiarity with Agile, Lean, or Six Sigma methodologies.

Salary & Benefits

Salary ranges vary by location. For example, McLean, VA offers between 109,000 and 124,400. Additional performance-based incentives and a comprehensive benefits package are provided.

Equal Opportunity

Capital One is an equal opportunity employer committed to diversity and a drug-free workplace. Required accommodations are available through Capital One Recruiting.

Key skills/competency

  • Data Analysis
  • Business Intelligence
  • Data Management
  • Innovation
  • Python
  • SQL
  • R
  • AWS
  • Spark
  • Data Quality
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How to Get Hired at Capital One

🎯 Tips for Getting Hired

  • Customize your resume: Tailor skills to data analytics at Capital One.
  • Emphasize technical skills: Highlight Python, SQL, R, AWS experience.
  • Prepare business cases: Discuss BI and data management projects.
  • Practice interview insights: Review common data analyst behavioral questions.

📝 Interview Preparation Advice

Technical Preparation

Review Python and SQL coding challenges.
Practice data visualization tool exercises.
Study AWS service implementations and best practices.
Refresh knowledge on data quality frameworks.

Behavioral Questions

Describe a challenging data project.
Explain teamwork on data solutions.
Share an experience with business intelligence.
Discuss managing data quality under pressure.

Frequently Asked Questions