Senior Data Engineer / Analytics Engineer

Capgemini Sogeti offers a flexible work approach, comprehensive healthcare, strong financial wellbeing programs, paid time off and holidays, paid parental leave, and thoughtful benefits that support family building, tutoring, and social well being. The environment emphasizes mentoring, coaching, and learning, with Active Employee Resource Groups and disaster relief support to help you thrive. This is paired with a collaborative culture that values diverse perspectives and continuous growth.

As a Senior Data Engineer / Analytics Engineer, you will design, build, and maintain scalable data pipelines and analytics solutions, including a semantic data layer and AI driven data products that empower business intelligence, data science, and advanced analytics.

Responsibilities

• Lead the design, development, and deployment of robust data pipelines that integrate data across diverse systems with reliability and scale.
• Define and uphold analytics engineering best practices, including coding standards, data governance, performance optimization, and automation strategies.
• Participate in code reviews, provide constructive feedback, and contribute to the team’s ongoing improvement in engineering methods.
• Design, build, and maintain ETL and ELT pipelines, reusable frameworks, and libraries to transform data from multiple sources into trusted data assets.
• Proactively monitor data pipelines to ensure high availability, reliability, and performance across data workflows.
• Implement CI/CD pipelines to streamline deployment, testing, and maintenance of analytics processes.
• Collaborate with data scientists, engineers, analysts, product managers, and business stakeholders to translate requirements into concrete technical specifications.
• Communicate complex technical concepts effectively to non technical stakeholders to align on data initiatives.

Requirements

• Hands-on experience with SQL, Python, dbt, and Snowflake.
• Proficiency with Git for version control and Airflow for workflow orchestration.
• A proven track record of designing and building scalable data pipelines and architectures.
• Strong knowledge of data governance, data quality assurance, and performance optimization in a data engineering context.
• Expertise in ETL/ELT processes, data modeling, and integrating data from multiple sources into a data warehouse.
• Experience implementing CI/CD workflows and tools for data engineering.
• Strong problem solving and analytical abilities, paired with the ability to collaborate effectively in a team environment.

Technologies: SQL, Python, dbt, Snowflake, Git, Airflow

About the role

The analytics engineering team within the Service Analytics and AI organization focuses on building curated data products by leveraging both structured and unstructured enterprise data sources. The role centers on enabling business intelligence, data science, and advanced analytics by delivering scalable data pipelines, a semantic data layer, and AI powered data products that drive business growth and improve customer experiences.

Life at Capgemini

• Flexible work
• Healthcare including dental, vision, mental health, and well being programs
• Financial wellbeing programs such as 401(k) and Employee Share Ownership Plan
• Paid time off and paid holidays
• Paid parental leave
• Family building benefits like adoption assistance, surrogacy, and cryopreservation
• Social well being benefits like subsidized back up child/elder care and tutoring
• Mentoring, coaching and learning programs
• Employee Resource Groups
• Disaster Relief

Salary range: For this role, the gross annual base salary range is $110,841 to $145,000 for a full time position. This reflects base pay and may be complemented by bonuses or incentives discussed during the hiring process; final offer depends on experience and qualifications.