Data Engineer 4 (Manager, IC)
About The Position
Capital One’s Enterprise Data Tech (EDT) organization manages data technology, platforms, and experiences across the company. Its mission is to make data easy to find, use, understand, govern, and protect throughout the data lifecycle, using platforms that support data pipelines, storage, and access. The organization is evolving its capabilities for AI and expanding its data platforms. The Data Engineer will design, build, and deliver cloud data solutions and applications, collaborating with Agile teams, product managers, software engineers, data analysts, and data scientists. The role focuses on scalable, resilient, secure, and operationally efficient data pipelines and platforms. It also includes influencing engineering practices, communicating technical concepts and outcomes to stakeholders, and sharing knowledge with the data engineering community.
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 4 years of experience in application development; internship experience does not count.
- At least 2 years of experience in distributed data.
- At least 2 years of experience with SQL.
- At least 2 years of experience with one programming language: Python, Java, or Scala.
- At least 2 years of experience in data pipeline design and development.
- At least 1 year of experience in data modeling and designing end-to-end data solutions using relational and non-relational database systems.
Nice To Haves
- 7 or more years of application development experience with demonstrated proficiency in Python, SQL, Scala, or Java.
- 4 or more years of hands-on experience designing, deploying, and operating data workloads in at least one public cloud environment: AWS, Microsoft Azure, or Google Cloud.
- 4 or more years of experience building or supporting distributed data or compute workloads using tools such as EMR, Spark, Glue, or Databricks.
- 4 or more years of experience designing, implementing, and operating real-time or streaming data pipelines.
- 2 or more years of experience with data observability tools such as Monte Carlo or Splunk, or data orchestration tools such as Airflow or Dagster.
- 4 or more years of experience working with unstructured or semistructured data using NoSQL databases such as MongoDB, Cassandra, or DynamoDB.
- 4 or more years of experience designing and supporting data warehousing solutions such as Snowflake or Redshift.
- 2 or more years of experience working in an Agile development environment.
- 2 or more years of experience developing user-centric reusable data products.
Responsibilities
- Collaborate across Agile teams to design, develop, test, implement, and support technical solutions using full-stack development tools and technologies.
- Influence developers, data analysts, and data scientists working with machine learning, distributed microservices, lakehouse architecture, and full-stack systems.
- Use programming languages such as Python and Spark, open-source relational and NoSQL databases, and cloud data warehousing platforms such as Databricks and Snowflake.
- Stay current with data technology trends, experiment with and learn new technologies, participate in technology communities, and mentor members of the data community.
- Collaborate with product managers and software engineers to deliver cloud-first data solutions.
- 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.
- Implement data security standards, including encryption at rest and in transit and fine-grained access controls, to support compliance with data privacy regulations.
Benefits
- Comprehensive health, financial, and other benefits supporting total well-being.
- Eligible for 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
Mid Level
