Data Analysis Manager - Strategy and Analytics

Capital One • McLean, VA

22h • $179,700 - $205,100 • Onsite

About The Position

Data is at the center of everything we do at Capital One. Your role as a Data Analyst on the team will heavily leverage your deep expertise in SQL and data transformation. You will be a creative data wrangler, comfortable with extracting, modeling, and transforming large, complex datasets to support our consumers. This requires more than just the ability to write complex, performant queries; you must also possess a thorough understanding of database structures, warehousing best practices, query profiling, and optimization techniques for data modeling and data governance. Ultimately, this is an analytics engineering role supporting not only analysts in the Strategy & Analytics team but a swathe of other data customers across a broader team who are hungry for data, metrics, and insights.

Requirements

• Currently has, or is in the process of obtaining a: Bachelor’s Degree in quantitative field (Statistics, Economics, Operations Research, Analytics, Mathematics, Computer Science or a related quantitative field) plus at least 6 years of experience performing data analytics, or Master’s Degree plus at least 4 years of experience performing data analytics with an expectation that required degree will be obtained on or before the scheduled start date.
• At least 4 years of experience performing professional data analysis work
• At least 4 years of experience performing programming

Nice To Haves

• Master’s Degree in a Science, Technology, Engineering, Mathematics discipline
• At least 7 years of professional data analysis work experience
• At least 4 years of experience with Python, R, Spark or SQL
• At least 1 year of experience in people management
• At least 1 years of project management experience
• At least 1 year of experience in Tableau
• Proficient utilizing and developing within AWS service
• On the leading edge of Analytical technology with a passion for the newest and most innovative tools.
• Strong problem solving and conceptual thinking abilities in addition to communication, interpersonal and leadership skills are also important.

Responsibilities

• Own the transformation layer, applying best practices to design and implement data cubes, warehouses, and other data models to best serve our users.
• Define, manage, and implement the analytics engineering and infrastructure roadmap.
• Level up our data models, infrastructure, and dashboard interfaces to drive effective self-service.
• Liaise with team members and other data customers to understand and meet their analytical needs.
• Drive quality metadata and data discovery with a semantic layer—for both AI and humans.
• Excited to work alongside AI tools, not just using them, but improving their outputs by rigorously reviewing, refining, and iterating on AI-generated code and analyses
• Act as a performing data steward. Define and enforce rigorous data governance standards while managing metadata frameworks to ensure data compliance and discoverability
• Drive a high level of data quality and observability of our data at all stages of the data lifecycle.
• Support modernization and migration initiatives from legacy reporting platforms.
• Perform unit tests and conduct reviews with other team members to make sure your code is rigorously designed, elegantly coded, and effectively tuned for performance
• Drive a single source of truth of trusted metrics and data that users can find and understand easily and make decisions with confidence.
• Drive current and future strategy by leveraging your analytical skills
• Assist with building and using models to test and validate data
• Work with vast amounts of data in new and evolving environments
• Leverage analytics to create a customer experience above our peers
• Be a part of the full life cycle of projects and see end results
• Collaborate across business units
• Work with top talent in a fast paced, entrepreneurial environment where analytics and good data are a top priority
• Experience real work life balance, with little travel involved
• Driving high data and code quality, consistency, and simplicity.
• Identifying and implementing process, data, and reporting improvements for the organization
• Working with large and complex databases containing millions to billions of records
• Improving operational efficiencies and effectiveness
• Conducting analysis to evaluate processes and tests
• Enhancing self-service offering with enhanced data cubes, dashboards, and AI interfaces
• Consulting on the design and implementation of new production and data storage systems

Benefits

• comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being
• performance based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI)

What This Job Offers

• Job Type: Full-time
• Career Level: Manager