
at Capgemini
ConsultanciesPosted 6 days ago
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**Databricks Engineer** designs, builds, and evolves data platforms, supporting Augmented Delivery use cases. Responsibilities include developing data pipelines and products within Databricks, building scalable data architectures like lakes, warehousing, and lakehouses, optimizing SQL and Python transformations, and standardizing engineering assets via Master Data Management (MDM). Requirements: - Bachelor's in CS, Engineering, Data Engineering, or related field. - Proven Data Engineering experience. - Expertise in Databricks, SQL, Python, data warehousing, and lakehouse architectures. - Data modelling, ETL/ELT, and MDM understanding. - Proficiency in APIs, data integration, Git, CI/CD, and modern development practices. - Strong stakeholder communication skills. Plus skills: MDM implementation, infrastructure/or multidisciplinary programme experience, real-time data architectures, data governance.
- Compensation
- Not specified
- City
- Not specified
- Country
- Romania
Currency: Not specified
Full Job Description
Currently, we are seeking a Data Engineer to design, build, and evolve these data platforms. This includes supporting both use case delivery and the development of a Master Data Management (MDM) capability to standardise and codify engineering assets across programmes.
Our client is a global professional services company delivering science-based, digitally enabled, end-to-end solutions from consulting and advisory to design and implementation across the worlds most complex infrastructure, advanced manufacturing, environmental and technology challenges.
Your Role:
- Design and develop data pipelines and data products within Databricks to support Augmented Delivery use cases.
- Build and maintain scalable data architectures, including data lakes, lakehouses, and data warehousing solutions.
- Develop and optimise SQL and Python-based data transformations.
- Support the development and implementation of Master Data Management (MDM) solutions for engineering asset standardisation and codification.
- Ensure data quality, consistency, and governance across platforms.
- Integrate data from multiple sources, enabling interoperability across engineering and digital systems.
- Collaborate with developers and digital engineering teams to enable data-driven use cases and automation.
- Work within modern development environments using DevOps practices, including CI/CD, version control, and testing.
- Participate in pair programming and collaborative development.
- Present data solutions and architectures, clearly articulating complex concepts to non-technical audiences.
- Contribute to data standards, models, and best practices across the programme.
Your Profile:
- Bachelors degree in Computer Science, Engineering, Data Engineering, or a related discipline (or equivalent experience).
- Experience working as a Data Engineer or in a similar role.
- Strong experience with Databricks (or similar modern data platforms), SQL, and Python.
- Experience with data warehousing and lakehouse architectures.
- Data modelling and ETL/ELT experience.
- Understanding of Master Data Management (MDM) principles.
- Familiarity with APIs and data integration patterns.
- Experience with Git-based version control.
- Understanding of CI/CD, DevOps, and modern development practices.
- Strong communication and stakeholder engagement skills.
Would be a plus:
- Experience implementing or supporting MDM solutions.
- Experience with engineering, BIM, or infrastructure data environments.
- Exposure to event-driven or real-time data architectures.
- Experience in large-scale infrastructure or multidisciplinary programmes.
- Familiarity with data governance frameworks and standards.




