Associate Data Engineer

Choosing Capgemini means choosing a company where you will be empowered to shape your career in the way you’d like, where you’ll be supported and inspired by a collaborative community of colleagues around the world, and where you’ll be able to reimagine what’s possible. Join us and help the world’s leading organizations unlock the value of technology and build a more sustainable, more inclusive world.

• Design, build, and maintain ETL/ELT pipelines using Databricks (PySpark, Delta Lake).
• Optimize pipelines for performance, cost, and scalability within GCP.
• Develop batch and streaming data processes using Spark Streaming and related technologies.
• Implement data solutions using Big Query, Cloud Storage, Dataflow, Cloud Composer, and Vertex AI.
• Apply best practices for cloud security, IAM configuration, monitoring, and cost optimization.
• Build and maintain data models including dimensional and data vault structures.
• Implement data quality frameworks, validation rules, and automated testing.
• Manage data versioning, governance, and lineage using tools like Unity Catalog or GCP Data Catalog.
• Collaborate with cross-functional teams to translate business requirements into technical designs.
• Provide technical guidance and support engineering best practices.
• Contribute to documentation, architectural diagrams, and knowledge-sharing materials.
• Databricks or GCP certifications (e.g., Data Engineer, Architect).
• Experience with Terraform or other Infrastructure‑as‑Code tools.
• Knowledge of ML workflows or MLOps frameworks.
• Familiarity with data governance tools such as Unity Catalog, Great Expectations, and dbt.
• Excellent problem-solving and analytical abilities.
• Strong communication skills with the ability to collaborate effectively across technical and non-technical teams.
• A growth mindset with a passion for continuous learning, innovation, and staying current with emerging technologies.

• 3+ years of experience as a Data Engineer or similar role.
• Strong hands-on experience with Databricks, including:
  • PySpark / Spark
  • Delta Lake
  • Databricks Workflows / Jobs
• Proficiency with GCP, including:
  • Big Query
  • Cloud Storage
  • Dataflow or Dataproc
• Strong coding skills in Python and SQL.
• Strong understanding of distributed systems, data warehousing, and data architecture principles.
• Experience with CI/CD tools such as Git Hub, Git Lab, or Azure Dev Ops.

The base compensation range for this role in the posted location is:$46,000 to $111,000.

Capgemini provides compensation range information in accordance with applicable national, state, provincial, and local pay transparency laws. The base compensation range listed for this position reflects the minimum and maximum target compensation Capgemini, in good faith, believes it may pay for the role at the time of this posting. This range may be subject to change as permitted by law.

The actual compensation offered to any candidate may fall outside of the posted range and will be determined based on multiple factors legally permitted in the applicable jurisdiction.

These may include, but are not limited to:
Geographic location, Education and qualifications, Certifications and licenses, Relevant experience and skills, Seniority and performance, Market and business consideration, Internal pay equity.

It is not typical for candidates to be hired at or near the top of the posted compensation range.

In addition to base salary, this role may be eligible for additional compensation such as variable incentives, bonuses, or commissions, depending on the position and applicable laws.

Capgemini offers a comprehensive, non-negotiable benefits package to all regular, full-time employees. In the U.S. and Canada, available benefits are determined by local policy and eligibility and may include:

• Paid time off based on employee grade (A-F), defined by policy:
  Vacation: 12-25 days, depending on grade, Company paid holidays, Personal Days, Sick Leave
• Medical, dental, and vision coverage (or provincial healthcare coordination in Canada)
• Retirement savings plans (e.g., 401(k) in the U.S., RRSP in Canada)
• Life and disability insurance
• Employee assistance programs
• Other benefits as provided by…