Staff Data Engineer

Join Capital One as a Staff Data Engineer (Director, IC - Card Tech) in a hybrid role based in McLean, VA. This position is designed for a technical leader who wants to shape next-generation data platforms, drive governed data solutions in the cloud, and multiply impact through end-to-end ownership, mentorship, and stakeholder influence. You will also have the opportunity to help build and expand the organization’s talent pipeline for Tech, both by mentoring internally and supporting external recruiting.

Compensation includes a performance-based incentive compensation package, which may include cash bonus(es) and/or long term incentives (LTI), plus a comprehensive, competitive, and inclusive set of health, financial, and other benefits.

Responsibilities

• Share consumer and engineering benefits to build awareness, increase knowledge, and drive adoption of modern technologies.
• Balance lending deep expertise with an inclusive environment where others’ ideas can be heard and championed, leveraging your skills to grow capabilities across the broader team.
• Promote engineering excellence by encouraging reuse and innersourcing solutions where possible.
• Communicate clearly and influence key stakeholders across the enterprise at all organizational levels.
• Act as a trusted advisor for a technology, platform, or capability domain, shaping use cases and implementation with a unified approach.
• Lead next-generation talent development for Tech by mentoring internal talent and actively recruiting external talent.
• Research and assess emerging trends in data, AI, and engineering, then translate findings into a roadmap for integrating relevant innovations into the overall data platform.
• Drive strategic alignment and integration decisions across multiple data systems and business units, championing a unified data architecture that supports seamless, scalable, governed data flow.
• Own the creation, management, and socialization of data strategy artifacts, including documentation such as data governance policies, architecture blueprints, and data product roadmaps.
• Serve as a technical force-multiplier by independently owning end-to-end design and coding for critical data projects while influencing architectural standards and mentoring junior engineers to increase team capability and output.

Requirements

• Bachelor’s Degree or higher in Computer Science or a related quantitative field (Statistics, Economics, Operations Research, Analytics, Mathematics, Engineering).
• At least 7 years of experience in data engineering.
• At least 3 years of experience in data architecture.
• At least 2 years building applications in AWS.
• At least 5 years programming with Python, Java, or Scala.
• At least 5 years designing and developing data pipelines.
• At least 3 years in data modeling and designing end-to-end data solutions using both relational and non-relational database systems.

Technologies

AWS, Python, Java, Scala, EMR, Spark, Glue, Databricks, Airflow, Dagster, Monte Carlo, Splunk, MongoDB, Cassandra, DynamoDB, Snowflake, Redshift, Microsoft Azure, Google Cloud, NoSQL

Preferred Qualifications

• Master’s Degree in Computer Science or a related field.
• 10+ years of experience in data engineering.
• 6+ years of data modeling experience.
• 2+ years of experience with ontology standards for defining a domain.
• 1+ year of experience deploying machine learning models.
• 10+ years of experience in application development with demonstrated proficiency in Python, SQL, Scala, or Java.
• 7+ years of hands-on experience designing, deploying, and operating data workloads in at least one public cloud environment (AWS, Microsoft Azure, or Google Cloud).
• 6+ years of experience building or supporting distributed data or compute workloads using tools such as EMR, Spark, Glue, or Databricks.
• 6+ years of experience designing, implementing, and operating real-time or streaming data pipelines.
• 4+ years of experience in data observability (e.g., Monte Carlo, Splunk) or data orchestration tools (e.g., Airflow, Dagster).
• 6+ years of experience with unstructured/semistructured data using NoSQL databases (e.g., MongoDB, Cassandra, DynamoDB).
• 6+ years of experience designing and supporting data warehousing solutions (e.g., Snowflake, Redshift).
• 4+ years of experience working in an Agile development environment.
• 4+ years of experience developing user-centric reusable data products.

Location, Salary, and Hybrid

• Location: McLean, VA (hybrid)
• Salary: USD 244,700 - 307,200 per year (McLean, VA: $269,100 - $307,200; Richmond, VA: $244,700 - $279,200)
• Hybrid policy: The role is designated as a hybrid position with required on-site presence at the designated office location.

Other

• Capital One may consider sponsoring a new qualified applicant for employment authorization for this position.
• This role is expected to accept applications for a minimum of 5 business days.
• No agencies please.
• Capital One is an equal opportunity employer (EOE, including disability/vet) committed to non-discrimination in compliance with applicable federal, state, and local laws.
• Capital One promotes a drug-free workplace.
• Capital One will consider for employment qualified applicants with a criminal history in a manner consistent with applicable laws regarding criminal background inquiries.