Senior Data Engineer

Senior Data Engineer

This position is required to work hybrid, 2 to 3 days in our local office.

• Contribute to the migration of legacy data warehouse to a Google Cloud-based data warehouse
• Collaborate with Data Product Managers, Data Architects to design, implement, and deliver successful data solutions
• Help architect data pipelines for the underlying data warehouse and data marts
• Design and develop very complex ETL pipelines in Google Cloud data environments
• Our legacy tech stack includes Teradata and new tech stack includes GCP Cloud Data Technologies like Big Query and Airflow and languages include SQL, Python
• Maintain detailed documentation of your work and changes to support data quality and data governance
• Support QA and UAT data testing activities
• Support deployment activities to higher environments
• Ensure high operational efficiency and quality of your solutions to meet SLAs and support commitment to our customers (Data Science, Data Analytics teams)
• Be an active participant and advocate of agile/scrum practice to ensure health and process improvements for your team

• 4 to 8+ years of data engineering experience developing large data pipelines in very complex environments
• Very strong SQL skills and ability to build very complex transformation data pipelines using a custom ETL framework in Google Big Query environment
• Exposure to Teradata and ability to understand complex Teradata BTEQ scripts
• Strong Python programming skills
• Strong skills on building Airflow jobs and debugging issues
• Ability to optimize queries in Big Query
• Hands-on experience with Google Cloud data technologies (GCS, Big Query, Dataflow, Pub/Sub, Data Fusion, Cloud Functions)

• Experience with cloud data warehouse technology Big Query
• Nice to have experience with Cloud technologies like GCP (GCS, Data Proc, Pub/Sub, Dataflow, Data Fusion, Cloud Functions)
• Nice to have exposure to Teradata
• Solid experience with job orchestration tools like Airflow and ability to build complex jobs
• Writing and maintaining large data pipelines using a custom ETL framework
• Ability to automate jobs using Python
• Familiarity with data modeling techniques and data warehousing standard methodologies and practices
• Very good experience with code version control repositories like Git Hub
• Good scripting skills, including Bash scripting and Python
• Familiar with Scrum and Agile methodologies
• Problem solver with strong attention to detail and excellent analytical and communication skills
• Ability to work in onsite/offshore model and able to lead a team

Data engineers are responsible for building reliable and scalable data infrastructure that enables organizations to derive meaningful insights, make data-driven decisions, and unlock the value of their data assets.

The role involves leading and managing a team of data engineers, overseeing data engineering projects, ensuring technical excellence, and fostering collaboration with stakeholders. They play a critical role in driving the success of data engineering initiatives and ensuring the delivery of reliable and high quality data solutions to support the organization's data-driven objectives.

Capgemini is an AI-powered global business and technology transformation partner, delivering tangible business value. We imagine the future of organizations and make it real with AI, technology and people. With our strong heritage of nearly 60 years, we are a responsible and diverse group of 420,000 team members in more than 50 countries. We deliver end-to-end services and solutions with our deep industry expertise and strong partner ecosystem, leveraging our capabilities across strategy, technology, design, engineering and business operations.

The Group reported 2024 global revenues of €22.1 billion.

Make it real |

: 396972

Posted on:
Jan 30, 2026

Experience Level: Experienced Professionals

Contract Type:
Permanent

Location:

New York, NY, US

Brand:
Capgemini

Professional Community:
Data & AI

Capgemini is an Equal Opportunity Employer encouraging diversity in the workplace. All qualified applicants will receive consideration for employment without regard to race, national origin, gender identity/expression, age, religion, disability, sexual orientation, genetics, veteran status, marital status or any other characteristic protected by law.