Data Engineer

Position: Data Engineer

Location: Mclean, VA

Duration: Long term contract


Note: Looking for Ex-Capital One Employee / Contractor

About the Role:

We are seeking an experienced Data Engineer to join our team supporting Capital One. The ideal candidate will have a strong background in building scalable data pipelines, modern cloud data platforms, and working with large-scale financial data. This role involves working closely with Capital One's data, analytics, and technology teams to design, implement, and optimize data solutions that enable advanced analytics and business insights.

Key Responsibilities:

• Design, develop, and maintain robust, scalable, and secure data pipelines for Capital One applications.
• Work with structured and unstructured data across cloud and on-premises environments.
• Implement data ingestion, transformation, and integration processes using modern ETL/ELT frameworks.
• Collaborate with data scientists, analysts, and product teams to enable data-driven decision-making.
• Ensure data quality, governance, and compliance with Capital One and regulatory standards.
• Optimize performance of large-scale data pipelines and storage solutions.
• Work in Agile teams, following CI/CD and DevOps best practices.

Required Skills & Experience:

• Strong experience in Data Engineering with hands-on development of ETL/ELT workflows.
• Expertise in Python, SQL, and Spark (PySpark/Scala).
• Proficiency in AWS Cloud Services (S3, Redshift, EMR, Glue, Lambda, etc.).
• Experience with Snowflake or other cloud-based data warehouses.
• Knowledge of data modeling, data lakes, and data warehouse design.
• Experience with Airflow, DBT, or similar orchestration tools.
• Strong understanding of CI/CD pipelines, Git, and DevOps practices.
• Prior exposure to financial services, banking, or credit domain is highly desirable.

Nice-to-Have Skills:

• Experience with Capital One-specific data platforms and tooling.
• Exposure to real-time streaming technologies (Kafka, Kinesis).
• Familiarity with machine learning pipelines.
• Strong problem-solving and communication skills.

Education:

• Bachelor's or Master's degree in Computer Science, Information Systems, Data Engineering, or related field.