Data Engineer 5 - Enterprise Risk Management

Capital One; McLean (VA); On-site; USD 140,000 - 180,000; Full time

Job summary

Capital One is seeking a Data Engineer 5 to join Enterprise Risk Management in McLean, VA. The role focuses on building cloud-first data solutions, leading data pipelines and collaborating across Agile teams to deliver scalable, robust data platforms for risk management.

You will mentor peers, drive architectural decisions, and work with Snowflake, Databricks, Spark, and NoSQL databases while advancing data observability and governance. Strong SQL and programming skills required.

Qualifications

• Bachelor's degree or higher in Computer Science or related quantitative field.
• 6+ years of application development experience.
• 4+ years in distributed data environments.
• 4+ years of SQL experience.
• 4+ years programming in Python, Java, or Scala.
• 4+ years designing and developing data pipelines.
• 2+ years data modeling with relational and non-relational databases.

Responsibilities

• Collaborate with Agile teams to design, develop, test, and support technical solutions.
• Lead a team of developers, data analysts and data scientists on ML and lakehouse projects.
• Build cloud-first data solutions using Python, Spark and cloud data warehouses.
• Mentor peers and stay current with data trends and new technologies.
• Deliver robust data solutions to empower customers and drive outcomes.
• Design scalable and maintainable data pipelines and platforms.
• Communicate data concepts and outcomes to stakeholders to achieve alignment.
• Drive large-scale data initiatives end-to-end and evaluate platform choices.

Skills

Python

SQL

Spark

Databricks

Snowflake

NoSQL

Education

Bachelor's Degree in Computer Science or related field

Tools

EMR

Airflow

Dagster

MongoDB

Cassandra

DynamoDB

Job description

Data Engineer 5 - Enterprise Risk Management

Do you love building and pioneering in the technology space? Do you enjoy solving complex business problems in a fast-paced, collaborative, inclusive and iterative delivery environment? At Capital One, you'll be part of a big group of makers, breakers, doers and disruptors who solve real problems and meet real customer needs. We are seeking Data Engineers who are passionate about marrying data with emerging technologies. In this role, you'll be at the forefront of driving a major transformation across Capital One.

What You’ll Do:

• Collaborate with and across Agile teams to design, develop, test, implement, and support technical solutions in full-stack development tools and technologies
• Influence a team of developers, data analysts and data scientists with deep experience in machine learning, distributed microservices, lakehouse architecture, and full-stack systems
• Utilize programming languages such as Python and Spark, along with open-source relational and NoSQL databases, and cloud-based data warehousing platforms including Databricks and Snowflake
• Share your passion for staying on top of trends in data, experimenting with and learning new technologies, participating in internal and external technology communities, and mentoring other members of the data community
• Collaborate with product managers and software engineers to deliver robust cloud-first data solutions that drive powerful experiences to help millions of Americans achieve financial empowerment
• Independently design, build and deliver world-class cloud data solutions and applications with little or no support from supervisors or managers
• Architect and enforce common data engineering design patterns to ensure code quality, maintainability, and reusability across data platforms and pipelines
• Serve as an ambassador for the data engineering team, communicating technical concepts and data outcomes clearly to both internal and external stakeholders to drive alignment and shared understanding
• Design and build data pipelines and platforms with a focus on scalability, resilience, and operational efficiency, ensuring robust performance under increasing data volume and business demands
• Serve as a force-multiplier for the team, balancing deep, hands-on technical contribution and innovation with mentoring and elevating the skills of peers and junior engineers
• Lead and execute large-scale, transformative data initiatives from end to end, independently driving critical architectural decisions and evaluating platform choices, such as Snowflake versus Databricks, based on technical and business requirements

Basic Qualifications:

• Bachelor's Degree or higher in Computer Science or a related quantitative field (Statistics, Economics, Operations Research, Analytics, Mathematics, Engineering)
• At least 6 years of experience in application development (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 experience programming with at least one of the following languages: 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 both relational and non-relational database systems

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

Capital One will consider sponsoring a new qualified applicant for employment authorization for this position.

The minimum and maximum full-time annual salaries for this role are listed below, by location. Please note that this salary information is solely for candidates hired to perform work within one of these locations, and refers to the amount Capital One is willing to pay at the time of this posting. Salaries for part-time roles will be prorated based upon the agreed