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Cluj-Napoca, RO
Actively hiring, first seen by us 20 hours agoData 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.
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Day 0
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From 13,754 similar postings that came down. Coming down is not always a hire.
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New Data Engineer postings at the employers we follow are up 7% over the last 6 weeks compared with the 6 before.
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.
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.
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
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.
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Cluj-Napoca, RO
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