Capital One is hiring a Data Engineer 4 to support its HR Tech transformation. In this onsite role in McLean, VA, you will help build cloud-first data solutions by designing scalable pipelines and platforms, collaborating with Agile teams, and applying strong security and compliance practices across the data lifecycle.
You will work with experienced engineers and data professionals to deliver reliable data capabilities that support product development and outcomes for millions of Americans, while also mentoring and sharing knowledge across the data engineering community.
What You’ll Do
- Collaborate with Agile teams to design, develop, test, implement, and support technical solutions across full-stack development tools and technologies
- Guide and influence a team of developers, data analysts, and data scientists with expertise spanning machine learning, distributed microservices, lakehouse architecture, and full-stack systems
- Build using Python and Spark, leveraging open-source relational and NoSQL databases, and cloud data warehousing platforms such as Databricks and Snowflake
- Stay current with data engineering trends through experimentation and continuous learning, including participation in internal and external technology communities and mentoring
- Partner with product managers and software engineers to deliver robust cloud-first data solutions that drive experiences supporting financial empowerment
- Independently design, build, and deliver cloud data solutions and applications with limited support from supervisors or managers
- Architect and enforce common data engineering design patterns to improve code quality, maintainability, and reuse across pipelines and platforms
- Design and build data pipelines and platforms with scalability, resilience, and operational efficiency to maintain performance as data volume and business demand grow
- Implement data security standards, including encryption at rest and in transit and fine-grained access control, to support compliance with data privacy regulations
- Act as a data engineering ambassador by clearly communicating technical concepts and data outcomes to internal and external stakeholders
Required Qualifications
- Bachelor's Degree or higher in Computer Science or a related quantitative field (Statistics, Economics, Operations Research, Analytics, Mathematics, Engineering)
- At least 4 years of experience in application development (internship experience does not apply)
- 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 both relational and non-relational databases
Technologies
- Python, Spark, Databricks, Snowflake, SQL, Java, Scala
- EMR, Glue, Airflow, Dagster
- Monte Carlo, Splunk
- AWS, Microsoft Azure, Google Cloud
- MongoDB, Cassandra, DynamoDB
- Redshift
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 (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 in data observability (e.g., Monte Carlo, Splunk) or data orchestration tools (e.g., Airflow, Dagster)
- 4+ years of experience working with unstructured or semistructured data using NoSQL databases (e.g., MongoDB, Cassandra, DynamoDB)
- 4+ years of experience designing and supporting data warehousing solutions (e.g., Snowflake, Redshift)
- 2+ years of experience working in an Agile development environment
- 2+ years of experience developing user-centric reusable data products
Compensation and Location
- Location: McLean, VA (onsite)
- Salary: $197,300 - $225,100 per year
- McLean, VA: $197,300 - $225,100 for Data Engineer 4
- Richmond, VA: $179,400 - $204,700 for Data Engineer 4
- This role is expected to accept applications for a minimum of 5 business days
- Incentives could be discretionary or non-discretionary depending on the plan
Benefits
- Comprehensive, competitive, and inclusive set of health, financial, and other benefits supporting total well-being
- Performance-based incentive compensation, which may include cash bonus(es) and/or long-term incentives (LTI)
Work Authorization
Capital One will not sponsor a new applicant for employment authorization or provide immigration-related support for this position (including H1B, F-1 OPT, F-1 STEM OPT, F-1 CPT, J-1, TN, E-3, O-1, and other forms of work authorization that require immigration support from an employer).
Additional Information
- No agencies please
- Capital One is an equal opportunity employer (EOE, including disability/veter) committed to non-discrimination in compliance with applicable federal, state, and local laws
- Capital One promotes a drug-free workplace
- Capital One will consider qualified applicants with a criminal history consistent with applicable laws
- If you require an accommodation, contact Capital One Recruiting at 1-800-304-9102 or RecruitingAccommodation@capitalone.com
- For technical support or questions about the recruiting process, email Careers@capitalone.com
Capital One notices: positions posted in Canada are for Capital One Canada, in the United Kingdom for Capital One Europe, and in the Philippines for Capital One Philippines Service Corp. (COPSSC).
