Data Engineer 5

Capital One is seeking a Data Engineer 5 to design, develop, test, implement, and support cloud-first data solutions while leading large-scale, end-to-end data initiatives.

Responsibilities

• Collaborate with and across Agile teams to design, develop, test, implement, and support technical solutions using full-stack development tools and technologies.
• Provide technical influence to a team of developers, data analysts, and data scientists with deep experience across machine learning, distributed microservices, lakehouse architecture, and full-stack systems.
• Develop with programming languages including Python and Spark, leveraging open-source relational and NoSQL databases and cloud data warehousing platforms such as Databricks and Snowflake.
• Stay current on data engineering trends through experimentation and continuous learning, including participation in internal and external technology communities and mentoring within the data community.
• Work with product managers and software engineers to deliver robust cloud-first data solutions that support financial empowerment outcomes for millions of Americans.
• Independently design, build, and deliver cloud data solutions and applications with minimal supervision from managers.
• Architect and enforce consistent data engineering design patterns to support code quality, maintainability, and reusability across data platforms and pipelines.
• Design and build data pipelines and platforms focused on scalability, resilience, and operational efficiency, maintaining performance as data volume and business demands increase.
• Serve as a data engineering ambassador by communicating technical concepts and data outcomes clearly to internal and external stakeholders.
• Act as a force-multiplier by combining hands-on engineering contributions and innovation with mentoring and skill elevation for peers and junior engineers.
• Lead and execute large-scale, transformative data initiatives end to end, including independent architectural decision-making and platform evaluation (for example, Snowflake versus Databricks) based on technical and business requirements.

Required Qualifications

• Bachelor’s Degree or higher in Computer Science or a related quantitative field (Statistics, Economics, Operations Research, Analytics, Mathematics, Engineering).
• 6+ years of experience in application development (internship experience does not apply).
• 4+ years of experience in distributed data.
• 4+ years of experience with SQL.
• 4+ years of programming with at least one of: Python, Java, or Scala.
• 4+ years of experience designing and developing data pipelines.
• 2+ years of experience in data modeling and designing end-to-end data solutions using both relational and non-relational database systems.

Technology Stack

Key technologies include Python, Spark, Databricks, Snowflake, SQL, and NoSQL databases. Additional tools and platforms mentioned include EMR, Glue, Airflow, Dagster, Monte Carlo, Splunk, AWS, Microsoft Azure, Google Cloud, plus data stores and ecosystems such as MongoDB, Cassandra, DynamoDB, Redshift, Scala, and Java, along with support for distributed microservices and lakehouse architecture.

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 in data observability (for example, Monte Carlo, Splunk) or data orchestration tools (for example, Airflow, Dagster).
• 5+ years of experience working with unstructured or semistructured data using NoSQL databases (for example, MongoDB, Cassandra, DynamoDB).
• 5+ years of experience designing and supporting data warehousing solutions (for example, Snowflake, Redshift).
• 3+ years of experience working in an Agile development environment.
• 3+ years of experience developing user-centric reusable data products.

Compensation and Benefits

• Salary range: USD 229,900 - 262,400 per year.
• This role is eligible for performance-based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI).
• Capital One provides a comprehensive, competitive, and inclusive set of health, financial, and other benefits to support total well-being.

Location

McLean, VA (onsite).