Data Engineer

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., * 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.

• 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.