Senior Data Engineer Ex Capital One

The ideal candidate will have strong expertise in designing, developing, and maintaining scalable data platforms, ETL/ELT pipelines, and cloud-based data solutions. We are seeking a highly experienced Senior Data Engineer with 10+ years of overall experience and prior Capital One experience .

Experience: 10+ Years
Mandatory Requirement:EX Capital One Only


Job Description


We are seeking a highly experienced Senior Data Engineer with 10+ years of overall experience and prior Capital One experience. The ideal candidate will have strong expertise in designing, developing, and maintaining scalable data platforms, ETL/ELT pipelines, and cloud-based data solutions.


Responsibilities

• Design, develop, and maintain scalable and reliable data pipelines and data processing solutions.
• Build and optimize ETL/ELT workflows for large-scale structured and unstructured datasets.
• Develop cloud-native data solutions, preferably using AWS services.
• Work extensively with Python, SQL, Spark/PySpark, and distributed data-processing technologies.
• Design and maintain data lakes, data warehouses, and enterprise data platforms.
• Implement data quality, validation, monitoring, governance, and security best practices.
• Optimize data pipelines and queries for performance, scalability, and cost efficiency.
• Collaborate with data architects, analysts, data scientists, product teams, and business stakeholders.
• Participate in architecture/design discussions and provide technical leadership and mentoring.
• Apply experience and engineering practices gained from working within Capital One’s technology/data environment.

Required Skills

• 10+ years of Data Engineering experience
• Previous Capital One experience – Mandatory
• Strong Python and SQL
• Strong Apache Spark / PySpark
• Hands-on experience with AWS and cloud-based data engineering
• Strong experience developing ETL/ELT and batch/streaming data pipelines
• Experience with large-scale data processing and distributed systems
• Experience with data lakes, data warehouses, and modern data architectures
• Strong understanding of data modeling, data quality, governance, and security
• Experience with CI/CD, Git, automated testing, and production deployment
• Excellent communication, troubleshooting, and stakeholder-management skills

Flexible work from home options available.