Senior Data Engineer - Remote, Cloud, Spark & Data Lakes

Tekvana Inc; Irving (TX); Hybrid; USD 140,000 - 180,000; Full time

Job summary

Tekvana Inc. seeks a Senior Data Engineer with 10+ years of experience and Capital One work history. You will design, build, and maintain scalable data platforms and ETL/ELT pipelines, leveraging AWS, Python, SQL, and Spark/PySpark in a cloud-first environment.

Collaborate with data scientists and business stakeholders, craft data lakes and warehouses, and ensure data quality, governance, and security. Flexible work-from-home options available.

Qualifications

• 10+ years of data engineering experience.
• Capital One experience required.
• Expertise in Python and SQL.
• Strong Spark / PySpark skills.
• Experience with AWS cloud data engineering.
• Knowledge of data lakes and data warehouses.
• Understanding of data modeling, governance, security.
• Experience with CI/CD, Git, and production deployment.

Responsibilities

• Design, develop, and maintain scalable data pipelines and data processing solutions.
• Build and optimize ETL/ELT workflows for large-scale datasets.
• Develop cloud-native data solutions, preferably AWS-based.
• Work with Python, SQL, Spark/PySpark, and distributed data-processing tech.
• Design data lakes, data warehouses, and enterprise data platforms.
• Implement data quality, governance, and security best practices.
• Optimize pipelines and queries for performance and cost.
• Collaborate with data architects, analysts, scientists, product teams.
• Provide technical leadership and mentorship.
• Apply Capital One tech/data practices to projects.

Skills

Data Engineering

Capital One exp

Python

SQL

Spark

PySpark

AWS

ETL/ELT

Data lakes

Data warehouses

Data modeling

Data governance

Security

CI/CD

Git

Testing

Production deployment

Job description

Tekvana Inc. seeks a Senior Data Engineer with 10+ years of experience and Capital One work history. You will design, build, and maintain scalable data platforms and ETL/ELT pipelines, leveraging AWS, Python, SQL, and Spark/PySpark in a cloud-first environment.

Collaborate with data scientists and business stakeholders, craft data lakes and warehouses, and ensure data quality, governance, and security. Flexible work-from-home options available.