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Vancouver, CA
Actively hiring, first seen by us todayThe role involves leading and managing a team of data engineers, defining and executing the data engineering strategy, and ensuring the effective delivery of data solutions. They provide technical expertise, drive innovation, and collaborate with stakeholders to deliver high quality, scalable, and reliable data infrastructure and solutions. The base compensation range for this role in the posted location is $102,523 to $183,760. 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.Read the full posting
Design and optimize scalable ETL/ELT pipelines using Databricks and PySpark
Build batch and real-time data ingestion frameworks
Implement orchestration workflows in Azure Data Factory, Airflow or Databricks Workflows
Optimize Databricks jobs and Spark applications for performance and cost
Monitor and troubleshoot production data pipelines
Design, develop, and optimize scalable ETL/ELT pipelines using Databricks and PySpark.
Build and maintain data ingestion frameworks for batch and real-time data processing.
Implement data orchestration workflows using tools such as Azure Data Factory, Airflow, or Databricks Workflows.
Optimize Databricks jobs and Spark applications for performance, scalability, and cost efficiency.
Monitor and troubleshoot production data pipelines and provide support for critical issues.
Actively hiringFirst seen by us today, still listed, and not a repost of an earlier posting.
These dates show when we found the posting. Check the employer’s website to confirm it is still accepting applications.
Day 0
Early. Similar jobs usually come down between day 6 and day 54.
From 11,115 similar postings that came down. Coming down is not always a hire.
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Hiring recordAdd 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.
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. We are seeking an experienced Databricks Data Engineer to design, develop, and maintain scalable data pipelines and cloud-based data platforms. The ideal candidate will have strong expertise in Databricks, PySpark, Python, SQL, Delta Lake, and cloud technologies (Azure/AWS), with experience building enterprise-scale data solutions that support analytics, reporting, and machine learning workloads. Key Responsibilities
Key Responsibilities - Design, develop, and optimize scalable ETL/ELT pipelines using Databricks and PySpark. - Build and maintain data ingestion frameworks for batch and real-time data processing. - Develop data models and implement data transformation logic using SQL and Python. - Leverage Delta Lake for data management, data quality, and performance optimization. - Implement data orchestration workflows using tools such as Azure Data Factory, Airflow, or Databricks Workflows. - Collaborate with data architects, analysts, data scientists, and business stakeholders to understand requirements and deliver solutions. - Optimize Databricks jobs and Spark applications for performance, scalability, and cost efficiency. - Implement data governance, security, and compliance best practices. - Monitor and troubleshoot production data pipelines and provide support for critical issues. - Participate in code reviews, documentation, and knowledge-sharing activities. Technical Skills:
Hands-on data pipeline development, ingest patterns in Azure Orchestration tools, ADF or Airflow SQL Denormalized Data modeling for big data systems
Strong/expert Spark (PySpark) Using Jupyter Notebooks, Colab or DataBricks (preferred) Hands-on data pipeline development, ingest patterns in Azure Orchestration tools, ADF or Airflow SQL
Technical Skills: Strong/expert Spark (PySpark) Using Jupyter Notebooks, Colab or DataBricks (preferred) Hands-on data pipeline development, ingest patterns in Azure
Complete your application on careers.capgemini.com. The employer’s form will show what is required.
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Yes. We’ve followed one other Lead Data Engineer job there since November 2026. It is still up.
New Data Engineer postings at the employers we follow are up 8% over the last 5 weeks compared with the 5 before.
Each bar is one week of new postings. The darkest bars are the last 5 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.
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.
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.
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.
We are seeking an experienced Databricks Data Engineer to design, develop, and maintain scalable data pipelines and cloud-based data platforms. The ideal candidate will have strong expertise in Databricks, PySpark, Python, SQL, Delta Lake, and cloud technologies (Azure/AWS), with experience building enterprise-scale data solutions that support analytics, reporting, and machine learning workloads.
Key Responsibilities
- Design, develop, and optimize scalable ETL/ELT pipelines using Databricks and PySpark.
- Build and maintain data ingestion frameworks for batch and real-time data processing.
- Develop data models and implement data transformation logic using SQL and Python.
- Leverage Delta Lake for data management, data quality, and performance optimization.
- Implement data orchestration workflows using tools such as Azure Data Factory, Airflow, or Databricks Workflows.
- Collaborate with data architects, analysts, data scientists, and business stakeholders to understand requirements and deliver solutions.
- Optimize Databricks jobs and Spark applications for performance, scalability, and cost efficiency.
- Implement data governance, security, and compliance best practices.
- Monitor and troubleshoot production data pipelines and provide support for critical issues.
- Participate in code reviews, documentation, and knowledge-sharing activities.
Technical Skills:
Strong/expert Spark (PySpark) Using Jupyter Notebooks, Colab or DataBricks (preferred)
Hands-on data pipeline development, ingest patterns in Azure
Orchestration tools, ADF or Airflow SQL
Denormalized Data modeling for big data systems
The base compensation range for this role in the posted location is $102,523 to $183,760.
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:
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.
Selected passages from the saved posting. Check the full description for conditions and exceptions.
The role involves leading and managing a team of data engineers, defining and executing the data engineering strategy, and ensuring the effective delivery of data solutions. They provide technical expertise, drive innovation, and collaborate with stakeholders to deliver high quality, scalable, and reliable data infrastructure and solutions. The base compensation range for this role in the posted location is $102,523 to $183,760. 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.
Vancouver, CA
Working pattern and location restrictions need checking in the full posting.
No clear work-authorization passage found. Eligibility is unconfirmed.