Data Engineer 4

Capital One • Wilmington, DE

2d • $179,400 - $204,700

About The Position

Capital One is seeking a Data Engineer passionate about combining data with emerging technologies to help drive a major transformation. The role works across Agile teams to develop and support cloud-first data solutions and applications that serve customers. It includes independently building cloud data solutions, influencing teams of developers, analysts, and data scientists, and communicating technical concepts and data outcomes to stakeholders.

The position designs scalable, resilient, and efficient data pipelines and platforms; establishes reusable data engineering design patterns; and implements security measures such as encryption and fine-grained access controls. Technologies mentioned include Python, Spark, relational and NoSQL databases, Databricks, and Snowflake. The role also involves staying current with data technology, participating in technology communities, and mentoring others.

Requirements

• Bachelor's degree or higher in Computer Science or a related quantitative field.
• At least 4 years of application development experience; internship experience does not apply.
• At least 2 years of experience in distributed data.
• At least 2 years of SQL experience.
• At least 2 years of experience with Python, Java, or Scala.
• At least 2 years of data pipeline design and development experience.
• 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+ years of application development experience with proficiency in Python, SQL, Scala, or Java.
• 4+ years of hands-on experience designing, deploying, and operating data workloads in a public cloud environment such as AWS, Microsoft Azure, or Google Cloud.
• 4+ years of experience building or supporting distributed data or compute workloads using tools such as EMR, Spark, Glue, or Databricks.
• 4+ years of experience designing, implementing, and operating real-time or streaming data pipelines.
• 2+ years of experience with data observability tools such as Monte Carlo or Splunk, or orchestration tools such as Airflow or Dagster.
• 4+ years of experience working with unstructured or semistructured data using NoSQL databases such as MongoDB, Cassandra, or DynamoDB.
• 4+ years of experience designing and supporting data warehousing solutions such as Snowflake or Redshift.
• 2+ years of experience working in an Agile development environment.
• 2+ years of experience developing user-centric reusable data products.

Responsibilities

• Collaborate with Agile teams to design, develop, test, implement, and support technical solutions.
• Influence developers, data analysts, and data scientists working with machine learning, distributed microservices, lakehouse architecture, and full-stack systems.
• Use programming languages, open-source relational and NoSQL databases, and cloud-based data warehousing platforms.
• Stay current with data trends and 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.
• Communicate technical concepts and data outcomes to internal and external stakeholders.
• 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 control.

Benefits

• Comprehensive, competitive, and inclusive health, financial, and other benefits supporting total well-being.
• Performance-based incentive compensation, which may include cash bonuses and/or long-term incentives.

What This Job Offers

• Job Type: Full-time
• Career Level: Senior