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Senior Data Engineer - Databricks

Pay
$89,400–166,398/year · BaseAnnual period assumed. Not guaranteed — pay source
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.
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Work setting
Not stated
Employment
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Before you apply

Employer’s visa record
4,980 H-1B petitions approved in fiscal 2024 and 2025For the employer as a whole. This posting doesn’t say whether the role is sponsored. US Citizenship and Immigration Services.

What you’ll work on

Full posting
  • 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.

From the employer’s posting
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.
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.
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).
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Posting record

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Actively hiringFirst seen by us today, still listed, and not a repost of an earlier posting.

Status in our records
Live
First seen by us
Nov 14, 2026today
Recorded sightings
2
Last seen by us
Nov 15, 2026

These dates show when we found the posting. Check the employer’s website to confirm it is still accepting applications.

How this job compares

Pay

In line with similar jobs

$89.4K–$166K against $127K–$190K, the middle half of what similar US postings state.

From 2,239 postings in the last year. Stated ranges, not salaries paid.

Time since we first saw it

Day 0

Early. Similar jobs usually come down between day 6 and day 56.

From 13,754 similar postings that came down. Coming down is not always a hire.

Capgemini Service SAS is hiring

284 open jobs

Open jobs by the week we first saw them, last 12 weeks.

Hiring record

See how this role fits your experience

Add your resume and we’ll mark which of these tools you already use, and point out anything in the posting that could rule you out.

  • Python
  • SQL
  • AWS
  • Azure
  • Databricks
  • Delta Lake
  • GCP
  • Terraform
  • PySpark
Where the posting names them
Skills and experience - 5-8 years of experience in Data Engineering.Strong proficiency in Python (PySpark) and SQL.Hands-on experience with: -
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.
- 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.
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.
- 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.
- 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.
- 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).
- 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.
- - Databricks Lakehouse Platform - Delta Lake
- Unity Catalog - Databricks Workflows - Structured Streaming
- 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)
- Databricks Lakehouse Platform - Delta Lake - Unity Catalog
- 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.
- 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)

Your next step

Complete your application on careers.capgemini.com. The employer’s form will show what is required.

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Has Capgemini Service SAS posted this job before?

Yes. We’ve followed one other Senior Data Engineer - Databricks job there since November 2026. It is still up.

  1. New YorkStill up after 10 days, first seen Nov 5
  2. This jobUp 1 day so far, first seen Nov 14

About Capgemini Service SAS

People
About 11,267 in 2024.Benefit plan filings (Form 5500)
Company
Listed as CAP.PA.
H-1B visas
771 approved for new hires in fiscal 2025.US Citizenship and Immigration Services

Demand for Data Engineer roles

New Data Engineer postings at the employers we follow are up 7% over the last 6 weeks compared with the 6 before.

Weekly new Data Engineer postings at the same employers, from the week of August 17 to the week of November 2. The fewest in a week was 860, the most 1,354, and the latest week had 1,335.
August 17Last week

Each bar is one week of new postings. The darkest bars are the last 6 weeks.

Counted from the hiring pages we’ve followed for at least five weeks, so employers we add don’t look like growth. Updated weekly.

About the role

We file this job under Data Engineer, by the work the posting describes.

Data engineers build and run the pipelines that copy data out of apps and outside services into a warehouse or lake, and fix them when a source changes or a load fails.

Expect SQL, Python, a cloud platform, a scheduler such as Airflow, and often tools for large data such as Spark or Kafka.

An analytics engineer works one step later, turning the raw data a data engineer lands into clean tables people can query.

US government figures for database architects

Median yearly pay, May 2025
$139,500
Expected change, 2025 to 2035
9.4% more jobsagainst 3.5% for all jobs

The government has no code for data engineers, so these figures are for the closest group, database architects, which includes data integration and data warehousing specialists.

Source: US Bureau of Labor Statistics, Occupational Employment and Wage Statistics (May 2025) and Employment Projections (2025 to 2035). Occupation code 15-1243.

Job description

View original posting ↗

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

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.

 

Disclaimers

Capgemini is an Equal Opportunity Employer encouraging inclusion in the workplace. Capgemini also participates in the Partnership Accreditation in Indigenous Relations (PAIR) program which supports meaningful engagement with Indigenous communities across Canada by promoting fairness, accessibility, inclusion and respect.  We value the rich cultural heritage and contributions of Indigenous Peoples and actively work to create a welcoming and respectful environment. 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.

This is a general description of the Duties, Responsibilities and Qualifications required for this position. Physical, mental, sensory or environmental demands may be referenced in an attempt to communicate the manner in which this position traditionally is performed. Whenever necessary to provide individuals with disabilities an equal employment opportunity, Capgemini will consider reasonable accommodations that might involve varying job requirements and/or changing the way this job is performed, provided that such accommodation does not pose an undue hardship. Capgemini is committed to providing reasonable accommodation during our recruitment process. If you need assistance or accommodation, please reach out to your recruiting contact.

Please be aware that Capgemini may capture your image (video or screenshot) during the interview process and that image may be used for verification, including during the hiring and onboarding process.

Click the following link for more information on your rights as an Applicant in the United States.  http://www.capgemini.com/resources/equal-employment-opportunity-is-the-law

 

Capgemini is a global business and technology transformation partner, helping organizations to accelerate their dual transition to a digital and sustainable world, while creating tangible impact for enterprises and society. It is a responsible and diverse group of 340,000 team members in more than 50 countries. With its strong over 55-year heritage, Capgemini is trusted by its clients to unlock the value of technology to address the entire breadth of their business needs. It delivers end-to-end services and solutions leveraging strengths from strategy and design to engineering, all fueled by its market leading capabilities in AI, generative AI, cloud and data, combined with its deep industry expertise and partner ecosystem.

 

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Pay
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.
Location & working pattern

New York, US

Working pattern and location restrictions need checking in the full posting.

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