Back to jobs

Data Python Engineer

Pay
Pay not listed
Work setting
Not stated
Employment
Not stated

Tools in this posting

  • Python
  • SQL
  • AWS
  • Azure
  • ClickHouse
  • Docker
  • GCP
  • Kafka
  • Kubernetes
  • Redshift
  • Snowflake
  • Spark
  • Terraform
  • Airflow
  • PySpark
Source — Tool mentions in context
Data Engineer (Python) At Capgemini Engineering, the world leader in engineering services, we bring together a global team of engineers, scientists, and architects to help the world’s most innovative companies unleash their potential. From autonomous cars to life-saving robots, our digital and software technology experts think outside the box as they provide unique R&D and engineering services across all industries. Join us for a career full of opportunities, where you can make a difference and where no two days are the same.
Job Description - Grade Specific Your profile: •Strong hands-on experience with Python, including development of production-grade software, data pipelines, APIs, and automation solutions •Experience designing and implementing ETL/ELT pipelines and scalable data processing solutions •Good knowledge of SQL, data modeling, query optimization, and relational databases •Experience with cloud-based data platforms and modern data architectures (AWS, Azure, or GCP) •Hands-on experience with Apache Airflow or similar workflow orchestration platforms •Experience working with Kafka or other event-driven and streaming technologies •Strong Linux fundamentals and experience supporting production environments •Familiarity with CI/CD practices, automated testing, Git workflows, and modern software delivery processes •Strong debugging, troubleshooting, and problem-solving capabilities •Ability to work independently and collaborate effectively within cross-functional teams Nice to have: •Experience with ClickHouse, Redshift, Snowflake, or other data warehousing technologies •Experience with Spark / PySpark •Experience with Terraform, Infrastructure as Code, and cloud automation •Knowledge of Docker and Kubernetes •Experience supporting large-scale production data platforms •Experience with AI/ML data pipelines, feature stores, or machine learning infrastructure •Knowledge of data governance, data quality frameworks, and metadata management
Your profile: •Strong hands-on experience with Python, including development of production-grade software, data pipelines, APIs, and automation solutions •Experience designing and implementing ETL/ELT pipelines and scalable data processing solutions •Good knowledge of SQL, data modeling, query optimization, and relational databases •Experience with cloud-based data platforms and modern data architectures (AWS, Azure, or GCP) •Hands-on experience with Apache Airflow or similar workflow orchestration platforms •Experience working with Kafka or other event-driven and streaming technologies •Strong Linux fundamentals and experience supporting production environments •Familiarity with CI/CD practices, automated testing, Git workflows, and modern software delivery processes •Strong debugging, troubleshooting, and problem-solving capabilities •Ability to work independently and collaborate effectively within cross-functional teams Nice to have: •Experience with ClickHouse, Redshift, Snowflake, or other data warehousing technologies •Experience with Spark / PySpark •Experience with Terraform, Infrastructure as Code, and cloud automation •Knowledge of Docker and Kubernetes •Experience supporting large-scale production data platforms •Experience with AI/ML data pipelines, feature stores, or machine learning infrastructure •Knowledge of data governance, data quality frameworks, and metadata management What you will love about working here? Scale & Impact:Work on a modern data platform that processes and delivers critical data across multiple business domains, enabling data-driven decisions, operational efficiency, and future AI initiatives. Modern Data Engineering:Build cloud-native data solutions leveraging streaming technologies, orchestration platforms, modern data architectures, and scalable engineering practices while solving complex technical challenges. Career Growth:Benefit from structured career paths, with opportunities to expand your expertise across data engineering, cloud technologies, platform engineering, analytics, and emerging AI/ML ecosystems.

Posting record

Report an error

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

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

Your next step

Check the employer’s posting for the current role and application details.

Applying through SAP SuccessFactors

  • Images (.jpg) aren’t accepted as a resume.

Already applied? Track this application

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 ↗

Data Engineer (Python)

At Capgemini Engineering, the world leader in engineering services, we bring together a global team of engineers, scientists, and architects to help the world’s most innovative companies unleash their potential. From autonomous cars to life-saving robots, our digital and software technology experts think outside the box as they provide unique R&D and engineering services across all industries. Join us for a career full of opportunities, where you can make a difference and where no two days are the same.


Your role:
As a Data Engineer, you will contribute to the development and evolution of a modern data platform that supports large-scale data collection, processing, analytics, and operational intelligence. Working in a collaborative Agile environment, you will design, build, and optimize data solutions that enable reliable, high-quality data delivery across business and engineering teams.


In this role you will play a key role in:
•Designing, building, and maintaining scalable ETL/ELT pipelines and data workflows
•Developing and supporting both batch and real-time streaming data solutions
•Improving platform reliability, monitoring, observability, and overall performance
•Building integrations between internal systems, cloud services, external platforms, and connected IoT devices
•Collaborating with software engineers, analysts, and platform teams to troubleshoot production issues and deliver new data capabilities
•Participating in technical design discussions, automation initiatives, CI/CD pipelines, and engineering best practices to ensure high-quality data services

Job Description - Grade Specific

Your profile:
•Strong hands-on experience with Python, including development of production-grade software, data pipelines, APIs, and automation solutions
•Experience designing and implementing ETL/ELT pipelines and scalable data processing solutions
•Good knowledge of SQL, data modeling, query optimization, and relational databases
•Experience with cloud-based data platforms and modern data architectures (AWS, Azure, or GCP)
•Hands-on experience with Apache Airflow or similar workflow orchestration platforms
•Experience working with Kafka or other event-driven and streaming technologies
•Strong Linux fundamentals and experience supporting production environments
•Familiarity with CI/CD practices, automated testing, Git workflows, and modern software delivery processes
•Strong debugging, troubleshooting, and problem-solving capabilities
•Ability to work independently and collaborate effectively within cross-functional teams

 

Nice to have:
•Experience with ClickHouse, Redshift, Snowflake, or other data warehousing technologies
•Experience with Spark / PySpark
•Experience with Terraform, Infrastructure as Code, and cloud automation
•Knowledge of Docker and Kubernetes
•Experience supporting large-scale production data platforms
•Experience with AI/ML data pipelines, feature stores, or machine learning infrastructure
•Knowledge of data governance, data quality frameworks, and metadata management

 

What you will love about working here?
Scale & Impact:Work on a modern data platform that processes and delivers critical data across multiple business domains, enabling data-driven decisions, operational efficiency, and future AI initiatives.
Modern Data Engineering:Build cloud-native data solutions leveraging streaming technologies, orchestration platforms, modern data architectures, and scalable engineering practices while solving complex technical challenges.
Career Growth:Benefit from structured career paths, with opportunities to expand your expertise across data engineering, cloud technologies, platform engineering, analytics, and emerging AI/ML ecosystems.

Learning & Development:Access continuous learning programs, technical training, certifications, and hands-on experience with leading data technologies, cloud platforms, and industry best practices.
Community & Support:Join a collaborative network of data engineers, software engineers, architects, and technology professionals who value knowledge sharing, mentorship, and technical excellence.
Flexibility & Balance:Hybrid working policies allow you to manage your time and your work base effectively while maintaining a healthy work-life balance.

 

Capgemini is an AI-powered global business and technology transformation partner, delivering tangible business value. We imagine the future of organizations and make it real with AI, technology, and people. With our strong heritage of nearly 60 years, we are a responsible and diverse group of over 420,000 team members in more than 50 countries.

Source details

View original posting ↗

Source notes

Source excerpts

Selected passages from the saved posting. Check the full description for conditions and exceptions.

Pay

No pay amount identified in the saved description.

Location & working pattern

Cluj-Napoca, RO

This passage needs a closer read in the full description.

Work authorization

No clear work-authorization passage found. Eligibility is unconfirmed.

AI answers unavailable

We couldn’t identify enough role detail in this saved description to support an AI answer. Read the full posting