Data Engineer 5 (Senior Manager, IC)
About The Position
Capital One is seeking a Data Engineer 5 (Senior Manager, IC) for Enterprise Data Tech (EDT), which manages data technology, platforms, and experiences across the company. EDT’s mission is to make data easy to find, use, understand, govern, and protect throughout the data lifecycle, while evolving its capabilities for AI and expanding its data platforms. In this role, you will build and deliver cloud-first data solutions and applications, lead major data initiatives, and make critical architecture and platform decisions. You will collaborate across Agile teams and with product managers and software engineers, contribute hands-on technical expertise, mentor peers, and communicate technical concepts and outcomes to stakeholders. The role focuses on scalable, resilient, and operationally efficient data pipelines and platforms, using technologies such as Python, Spark, Databricks, Snowflake, relational databases, and NoSQL databases.
Requirements
- Bachelor's degree or higher in Computer Science or a related quantitative field, such as Statistics, Economics, Operations Research, Analytics, Mathematics, or Engineering.
- At least 6 years of application development experience; internship experience does not apply.
- At least 4 years of experience in distributed data.
- At least 4 years of experience with SQL.
- At least 4 years of programming experience with 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 relational and non-relational database systems.
Nice To Haves
- Master’s degree in Computer Science or a related field.
- 8 or more years of experience in data engineering.
- 5 or more years of hands-on experience designing, deploying, and operating data workloads in AWS.
- 5 or more years of experience building or supporting distributed data or compute workloads using tools such as EMR, Spark, Glue, or Databricks.
- 5 or more years of experience designing, implementing, and operating real-time or streaming data pipelines.
- 5 or more years of experience working with unstructured or semistructured data using NoSQL databases such as MongoDB, Cassandra, or DynamoDB.
- 5 or more years of experience designing and supporting data warehousing solutions such as Snowflake or Redshift.
- 4 or more years of data modeling experience.
- 3 or more years of experience working in an Agile development environment.
- 3 or more years of experience developing user-centric reusable data products.
- 3 or more years of experience working on data observability tools such as Monte Carlo or Splunk, or data orchestration tools such as Airflow or Dagster.
Responsibilities
- Collaborate with Agile teams to design, develop, test, implement, and support technical solutions using full-stack development tools and technologies.
- Influence and work with developers, data analysts, and data scientists experienced in machine learning, distributed microservices, lakehouse architecture, and full-stack systems.
- Use programming languages and platforms such as Python, Spark, relational and NoSQL databases, Databricks, and Snowflake.
- Stay current with data technology trends, experiment with and learn new technologies, participate in technology communities, and mentor other data professionals.
- Collaborate with product managers and software engineers to deliver cloud-first data solutions that support customer experiences.
- Independently design, build, and deliver cloud data solutions and applications with little or no supervisory support.
- Architect and enforce common data engineering design patterns to support code quality, maintainability, and reusability across platforms and pipelines.
- Communicate technical concepts and data outcomes to internal and external stakeholders to promote alignment and shared understanding.
- Design and build scalable, resilient, and operationally efficient data pipelines and platforms.
- Contribute hands-on technical work and innovation while mentoring and developing peers and junior engineers.
- Lead large-scale data initiatives end to end, make architectural decisions, and evaluate platforms such as Snowflake and Databricks against technical and business requirements.
Benefits
- Comprehensive health, financial, and other benefits supporting total well-being.
- Performance-based incentive compensation, which may include cash bonuses and/or long-term incentives.
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What This Job Offers
Job Type
Full-time
Career Level
Senior
