Data Engineer 4 (Manager IC) Risk Tech

We are seeking a Data Engineer 4 (Manager IC) to join our Risk Tech team at Capital One. As a Data Engineer, you will be responsible for designing, developing, testing, and implementing technical solutions in full-stack development tools and technologies.

In this role, you will collaborate with Agile teams to drive a major transformation across Capital One, focusing on building data-driven tools that use machine learning to prevent risks and automatically detect issues.

Key responsibilities include:

• Collaborating with teams to design, develop, test, and implement technical solutions
• Influencing a team of developers, data analysts, and data scientists
• Utilizing programming languages such as Python and Spark, along with open-source relational and NoSQL databases, and cloud-based data warehousing platforms
• Sharing knowledge of trends in data and experimenting with new technologies
• Collaborating with product managers and software engineers to deliver robust cloud-first data solutions
• Designing, building, and delivering world-class cloud data solutions and applications
• Architecting and enforcing common data engineering design patterns
• Serving as an ambassador for the data engineering team
• Designing and building data pipelines and platforms with a focus on scalability, resilience, and operational efficiency
• Implementing data security standards

Requirements:

• Bachelor's Degree or higher in Computer Science or a related quantitative field
• At least 4 years of experience in application development
• 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

Preferred qualifications:

• 7+ years of experience in application development with demonstrated proficiency in Python, SQL, Scala, or Java
• 4+ years of hands-on experience designing, deploying, and operating data workloads in at least one public cloud environment
• 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 working on data observability or data orchestration tools
• 4+ years of experience working with unstructured or semi-structured data using NoSQL databases
• 4+ years of experience designing and supporting data warehousing solutions
• 2+ years of experience working in an Agile development environment
• 2+ years of experience developing user-centric reusable data products

Salary ranges:

• McLean, VA: $197,300 - $225,100
• New York, NY: $215,200 - $245,600
• Richmond, VA: $179,400 - $204,700