Description
We are seeking Data Engineers who are passionate about marrying data with emerging technologies. In this role, you’ll be at the forefront of driving a major transformation across Capital One.
You will collaborate with and across Agile teams to design, develop, test, implement, and support technical solutions in full-stack development tools and technologies. You will influence a team of developers, data analysts and data scientists with deep experience in machine learning, distributed microservices, lakehouse architecture, and full-stack systems.
Responsibilities:
- Collaborate with product managers and software engineers to deliver robust cloud-first data solutions that drive powerful experiences to help millions of Americans achieve financial empowerment
- Independently design, build and deliver world-class cloud data, API and MCP solutions and applications with little or no support from supervisors or managers
- Architect and enforce common data engineering design patterns to ensure code quality, maintainability, and reusability across data platforms and pipelines
- Serve as an ambassador for the data engineering team, communicating technical concepts and data outcomes clearly to both internal and external stakeholders to drive alignment and shared understanding
- Design and build data pipelines and platforms with a focus on scalability, resilience, and operational efficiency, ensuring robust performance under increasing data volume and business demands
- Serve as a force-multiplier for the team, balancing deep, hands-on technical contribution and innovation with mentoring and elevating the skills of peers and junior engineers
- Lead and execute large-scale, transformative data initiatives from end to end, independently driving critical architectural decisions and evaluating platform choices, such as Snowflake versus Databricks, based on technical and business requirements
Basic Qualifications:
- Bachelor's Degree or higher in Computer Science or a related quantitative field (Statistics, Economics, Operations Research, Analytics, Mathematics, Engineering)
- At least 6 years of experience in application development
- At least 4 years of experience in distributed data
- At least 4 years of experience with SQL
- At least 4 years of experience programming with at least one of the following languages: Python, Java, or Scala
- At least 4 years of experience designing and developing data pipelines
- At least 2 years of experience in data modeling and designing end-to-end data solutions using both relational and non-relational database systems
Preferred Qualifications:
- Master’s Degree in Computer Science or a related field
- 8+ years of experience in data engineering
- 4+ years of data modeling experience
- 9+ years of experience in application development with demonstrated proficiency in Python, SQL, Scala, or Java
- 5+ years of hands-on experience designing, deploying and operating data workloads in at least one public cloud environment (AWS, Microsoft Azure, or Google Cloud)
- 5+ years of experience building or supporting distributed data or compute workloads using tools such as EMR, Spark, Glue, or Databricks
- 5+ years of experience designing, implementing, and operating real-time or streaming data pipelines
- 3+ years of experience working on data observability (e.g., Monte Carlo, Splunk) or data orchestration tools (e.g., Airflow, Dagster)
- 5+ years of experience working with unstructured or semistructured data using NoSQL databases (e.g., MongoDB, Cassandra, DynamoDB)
- 5+ years of experience designing and supporting data warehousing solutions (e.g., Snowflake, Redshift)
- 3+ years of experience working in an Agile development environment
- 3+ years of experience developing user-centric reusable data products
Benefits:
- Comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being