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.

Job Location

This job is local to Nashville TN.

About the job you're considering

We are seeking a skilled Data Engineer with hands-on experience in Databricks and Google Cloud Platform (GCP) to design, build, and optimize data pipelines and analytics solutions. The ideal candidate will have a strong background in distributed data processing, cloud architecture, and data modeling. This role partners closely with data analysts, data scientists, and business stakeholders to deliver scalable, reliable, and high‑quality data products.

Your role

• Design, build, and maintain ETL/ELT pipelines using Databricks (PySpark, Delta Lake).
• Optimize pipelines for performance, cost efficiency, and scalability within GCP.
• Develop batch and streaming data processes using Spark Streaming, and related technologies.
• Implement data solutions leveraging GCP services such as BigQuery, Cloud Storage, Dataflow,  Cloud Composer, and Vertex AI integrations.
• Apply best practices for cloud security, IAM configuration, monitoring, and cost management.
• Build and maintain data models, including dimensional modeling and data vault structures.
• Implement data quality frameworks, validation rules, and automated testing.
• Manage data versioning, governance, and lineage using tools such as Unity Catalog or GCP Data Catalog.
• Partner with cross‑functional teams to gather requirements and translate them into technical designs.
• Provide technical guidance and influence engineering best practices across the team.
• Contribute to documentation, architectural diagrams, and knowledge sharing

 

 

 

Skills and experience

• 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:
• BigQuery
• Cloud Storage
• Dataflow or Dataproc
• Strong coding skills in Python and SQL.
• Solid understanding of distributed systems, data warehousing, and data architecture principles.
• Experience with CI/CD tools (GitHub, GitLab, Azure DevOps, or similar).

 

Preferred Qualifications

• 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 (Unity Catalog, Great Expectations, dbt, etc.).

 

 

 

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-