Sr. Staff Data Engineer (Remote -Eligible)

Capital One is a financial services company focused on technology-driven banking solutions. The Senior Staff Data Engineer will lead the technical strategy for enterprise data pipelines and sharing capabilities, driving scalable architecture, operational excellence, and innovation. The role also involves hands-on development, stakeholder influence, mentoring, recruiting, and shaping enterprise data standards and roadmaps.

Responsibilities:

• Build awareness, increase knowledge and drive adoption of modern technologies, sharing consumer and engineering benefits to gain buy-in
• Strike the right balance between lending expertise and providing an inclusive environment where others’ ideas can be heard and championed; leverage expertise to grow skills in the broader Capital One team
• Promote a culture of engineering excellence, using opportunities to reuse and innersource solutions where possible
• Effectively communicate with and influence key stakeholders across the enterprise, at all levels of the organization
• Operate as a trusted advisor for a specific technology, platform or capability domain, helping to shape use cases and implementation in a unified manner
• Lead the way in creating next-generation talent for Tech, mentoring internal talent and actively recruiting external talent to bolster Capital One’s Tech talent
• Drive the strategic direction of the data engineering practice by continuously researching and assessing emerging trends in data, AI, and engineering, and developing a roadmap to integrate relevant innovations into the overall data platform
• Lead strategic alignment and integration decisions across multiple data systems and business units, championing a unified data architecture that supports seamless, scalable, and governed data flow across the organization
• Own the creation, management, and socialization of data strategy artifacts, ensuring comprehensive documentation is available to inform and guide enterprise-level decisions and initiatives (e.g., data governance policies, architecture blueprints, data product roadmaps)
• Serve as a technical "force-multiplier," independently owning the end-to-end design and coding of critical data projects while influencing architectural standards and mentoring junior engineers to scale the team's capabilities and output

Requirements:

• Bachelor's Degree in Computer Science or a related quantitative field (Statistics, Economics, Operations Research, Analytics, Mathematics, Engineering)
• At least 9 years of experience in data engineering
• At least 5 years of experience in data architecture
• At least 3 years of experience building applications in AWS
• At least 7 years of experience programming with at least one of the following languages: Python, Java, or Scala
• At least 6 years of experience designing and developing data pipelines
• At least 4 years of experience in data modeling and designing end-to-end data solutions using both relational and non-relational database systems
• Master's Degree in Computer Science or a related field
• 11+ years of experience in data engineering
• 8+ years of data modeling experience
• 3+ years of experience with ontology standards for defining a domain
• 2+ years of experience deploying machine learning models
• 12+ years of experience in application development with demonstrated proficiency in Python, SQL, Scala, or Java
• 8+ years of hands-on experience designing, deploying and operating data workloads in at least one public cloud environment (AWS, Microsoft Azure, or Google Cloud)
• 8+ years of experience building or supporting distributed data or compute workloads using tools such as EMR, Spark, Glue, or Databricks
• 8+ years of experience designing, implementing, and operating real-time or streaming data pipelines
• 6+ years of experience working on data observability (e.g., Monte Carlo, Splunk) or data orchestration tools (e.g., Airflow, Dagster)
• 8+ years of experience with unstructured/semistructured data using NoSQL databases (e.g., MongoDB, Cassandra, DynamoDB)
• 8+ years of experience designing and supporting data warehousing solutions (e.g., Snowflake, Redshift)
• 6+ years of experience working in an Agile development environment
• 6+ years of experience developing user-centric reusable data products