Capgemini

Data Engineer - Azure, Databricks

Capgemini$112K — $148K *
Information Technology
5 - 7 years of experience
Job Overview by Ladders

Qualifications

  • 6-7 years of experience in data engineering, focusing on Azure Data Factory/Synapse and Databricks.
  • Hands-on proficiency with PySpark and SQL, including strong debugging skills.
  • Prior experience in marketing technology (Martech) is essential.
  • Solid understanding of ITIL processes, especially incident and change management.
  • Familiarity with Azure Monitor, Log Analytics, and CI/CD platforms like Azure DevOps.
  • Excellent analytical, communication, and documentation skills.

Responsibilities

  • Provide multi-level production support for Azure and Databricks data systems.
  • Troubleshoot ingestion, transformation, and scheduling failures for data pipelines.
  • Conduct root-cause analysis to implement permanent fixes and maintain documentation.
  • Monitor system health, performance, and costs using Azure tools.
  • Optimize performance of Spark/Databricks workloads and handle cluster tuning.
  • Execute controlled production changes and engage in incident management processes.
  • Collaborate with teams to enhance automation and platform reliability.

Benefits

  • Paid time off based on employee grade, including vacation, sick leave, and personal days.
  • Comprehensive medical, dental, and vision coverage.
  • Retirement savings plans, such as a 401(k).
  • Life and disability insurance options available.
  • Employee assistance programs offered.
  • Additional benefits may vary by local policy.
Full Job Description
Job Location: The preferance for the location is Cinncinnati Ohio but it can be remote as well. About the job youre considering Capgemini is looking to hire a senior Azure Databricks Data Engineer with Martech experience in Cinncinnati Ohio. your role
  • Provide L1.5, L2, and L3 production support for Azure and Databricks-based data pipelines and applications.
  • Troubleshoot failures related to ingestion, transformations, scheduling, performance, and schema drift.
  • Conduct root-cause analysis, implement permanent fixes, and maintain runbooks, SOPs, and knowledge articles.
  • Monitor system health, SLAs, job performance, and platform costs using Azure and Databricks observability tools.
  • Optimize Spark/Databricks workloads including cluster tuning, Delta Lake optimization, and job performance enhancements.
  • Execute controlled production changes and participate in incident, problem, and change management processes.
  • Collaborate with engineering, operations, and business teams to implement automation and drive platform reliability.
Skills and experience
  • 6-7 years of experience in data engineering with strong expertise in Azure Data Factory/Synapse, ADLS Gen2, Azure SQL, Key Vault, and Databricks (Spark, Delta Lake, Unity Catalog).
  • Hands-on proficiency in PySpark and SQL, with strong debugging skills for production data pipelines.
  • Martech experience
  • Good understanding of ITIL processes including Incident, Problem, and Change Management.
  • Experience with Azure Monitor, Log Analytics, and CI/CD platforms (Azure DevOps/Git).
  • Strong analytical, communication, and documentation skills; ability to work in on-call or high-severity incident environments.
The base compensation range for this role in the posted location is: $112,763 - $148,000. 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 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 Capgeminis 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.

About Capgemini

Capgemini is a global leader in consulting, digital transformation, technology and engineering services. The company is headquartered in Paris, France and operates in over 50 countries. Capgemini provides a range of services including strategy and transformation, application services, technology services, and engineering services. The company serves clients in a variety of industries including automotive, consumer products, financial services, healthcare, and retail.
Learn more about Capgemini
Industry
Founded
1967
NASDAQ

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