Job Location
Troy, MI (Onsite Requirement)
Candidates must be able to work onsite at the customer location in Troy, MI a minimum of four (4) days per week.
About the job you're considering
We are seeking a highly skilled **Senior Databricks Data Engineer** with 5-8 years of experience in data engineering and cloud-based data platforms. The ideal candidate will have strong hands-on expertise in the Databricks ecosystem, including PySpark, Delta Lake, Unity Catalog, Structured Streaming, and Databricks Workflows. This role will be responsible for designing, developing, and optimizing scalable data solutions that support analytics, machine learning, and generative AI initiatives.
The successful candidate will work closely with data architects, data scientists, business stakeholders, and application teams to build modern lakehouse architectures and deliver high-performance data pipelines.
Your role
- Design, develop, and maintain scalable batch and real-time data pipelines using **PySpark, SQL, Delta Lake, and Auto Loader**.
- Build robust ETL/ELT frameworks to ingest, transform, and process large-scale datasets from multiple sources.
- Implement data quality checks, monitoring, and pipeline optimization to ensure reliability and performance.
- Design and manage modern **Databricks Lakehouse** solutions using Medallion Architecture (Bronze, Silver, Gold layers).
- Develop and maintain Delta Lake tables while ensuring optimal query performance.
- Perform performance tuning using Databricks best practices, (e.g. Photon Engine,Liquid Clustering, Partitioning)
- Configure and administer **Unity Catalog** to manage data governance across the enterprise.
- Implement catalog, schema, table, row-level, and column-level security controls.
- Enable data lineage, auditing, and compliance requirements across the data platform.
- Develop and maintain workflows using **Databricks Workflows**.
- Manage deployment processes using **Databricks Asset Bundles (DABs)**.
- Implement CI/CD pipelines leveraging GitHub, GitLab, and DevOps best practices.
- Provision and manage infrastructure using **Terraform** and Infrastructure-as-Code methodologies.
- Prepare and curate datasets for machine learning and generative AI applications.
- Support feature engineering and feature store implementations.
- Enable vector search and retrieval capabilities to support large language model (LLM) solutions and AI-driven use cases.
- Collaborate with Data Science and AI teams to operationalize ML workloads.
Skills and experience
- 5-8 years of experience in Data Engineering.Strong proficiency in **Python (PySpark)** and **SQL**.Hands-on experience with:
- Databricks Lakehouse Platform
- Delta Lake
- Unity Catalog
- Databricks Workflows
- Structured Streaming
- Auto Loader
- Experience designing and supporting large-scale enterprise data platforms.
- Strong understanding of data modeling, data warehousing, and ETL/ELT design patterns.
- Experience implementing CI/CD pipelines, version control, and automated testing practices.
- Hands-on experience with **Git, GitHub/GitLab, Terraform, and pytest**.
- Experience working with at least one major cloud platform: (Azure, GCP, AWS)
The base compensation range for this role in the posted location is: $89,400 - $166,398.
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 local policy and eligibility
**Important Notice:** Compensation (including bonuses, commissions, or other forms of incentive pay) is not considered earned, vested, or payable until it becomes due under the terms of applicable plans or agreements and is subject to Capgemini's discretion, consistent with applicable laws. The Company reserves the right to amend or withdraw compensation programs at any time, within the limits of applicable legislation.
