Senior Data Engineering Lead - ETL & Data Platform

Capgemini; Dallas (TX); On-site; USD 99,000 - 141,000; Full time

Benefits offered by this job

Paid time off

Medical, dental, and vision coverage

Retirement savings plans

Life and disability insurance

Employee assistance programs

Other benefits as provided by local政策

Job summary

Capgemini is seeking a Data Engineering Lead in Dallas, TX to design, develop, and maintain scalable data pipelines. You will steer ETL/ELT workflows using Airflow and Databricks, and oversee data warehousing with Snowflake and SQL.

The role includes mentoring engineers and ensuring production readiness across teams. Join Capgemini to collaborate with cross-functional teams, drive engineering best practices, and contribute to high-quality data solutions in a global technology landscape.

Qualifications

• 10-12+ years of Data Engineering experience.
• Experience in production Support environment with rotational shift.
• Experience with Agile methodologies, Git, and CI/CD practices.

Responsibilities

• Design, develop, and maintain data pipelines using Apache Airflow DAGs.
• Build and optimize ETL/ELT workflows using Databricks (PySpark/Spark).
• Develop and manage data warehousing solutions in Snowflake and SQL.
• Lead technical design, code reviews, performance tuning, and production support.
• Collaborate with cross-functional teams to deliver reliable and high-quality data solutions.
• Mentor team members and drive engineering best practices.

Skills

Data Engineering

Production Support

Agile methodologies

Git

CI/CD

Tools

Apache Airflow

Databricks

PySpark

Snowflake

SQL

Job description

Capgemini is seeking a Data Engineering Lead in Dallas, TX to design, develop, and maintain scalable data pipelines. You will steer ETL/ELT workflows using Airflow and Databricks, and oversee data warehousing with Snowflake and SQL.

The role includes mentoring engineers and ensuring production readiness across teams. Join Capgemini to collaborate with cross-functional teams, drive engineering best practices, and contribute to high-quality data solutions in a global technology landscape.