Rapidcircle·12 hours ago
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Migration & Modernization Data Engineer
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What you'll do
- Build reusable migration accelerators, templates, utilities, libraries and reference implementations for EDP onboarding.
- Refactor legacy data pipelines, data models and data products into scalable Lakehouse and Medallion architectures.
- Develop production-ready data pipelines using Databricks, Spark, Python/Scala, SQL and DBT.
- Define engineering patterns, standards and best practices for consistent migration and modernization delivery.
- Support data validation, reconciliation, testing, performance optimisation and operational readiness.
- Act as a technical consultant to business migration teams throughout assessment, planning and execution.
- Review current-state pipelines and data models, then recommend practical migration and refactoring approaches.
- Facilitate technical workshops, design reviews and migration planning discussions with business, architects and engineers.
- Help teams adopt EDP platform capabilities, governance, security and engineering standards.
What they're looking for
- Databricks: notebooks, workflows, jobs, Delta Lake, Unity Catalog and Lakehouse implementation.
- Apache Spark, Python/Scala and advanced SQL for scalable data engineering and optimisation.
- DBT for modelling, transformations, testing, documentation and deployment practices.
- Modern data architecture: ETL/ELT, batch/streaming, Medallion design, data products and enterprise data platforms.
- Data formats and modelling: Parquet, JSON, CSV, XML, dimensional modelling and analytics-ready structures.
- Ability to use GenAI and agentic AI to accelerate migration, refactoring, code conversion and documentation.
- Experience or strong understanding of building AI agents, copilots or automation assistants for engineering teams.
- Prompt engineering, AI-assisted development and workflow automation to improve delivery productivity.
- Ability to identify migration tasks that can be automated using AI, scripts, reusable tools or engineering frameworks.
Nice to have
- CI/CD, DevOps and Agile delivery experience in enterprise data engineering environments.
- Exposure to Power BI, self-service analytics, Data Mesh and data product management concepts.
- Strong stakeholder engagement, communication, documentation and problem-solving skills.
- Ability to manage competing priorities with a continuous learning mindset and strong ownership.
Summarised by NextRaise from the employer’s description, which follows in full below.
Full description from employer
Making a difference and driving positive change is what we do every day at Rapid Circle. Our Cloud Pioneers help our clients in their digital transformation. Are you someone who goes for constant, positive change? Then this vacancy is for you!
As a Cloud Pioneer at Rapid Circle, you will work with our customers on different projects. For example, making impact in the healthcare sector, by making research data safely available. But also, awesome projects in the manufacturing or energy market make this job very challenging.
At Rapid Circle we are curious and are constantly improving our expertise to help customers find their way in a rapidly changing world. We share our knowledge and discover new ways to learn.
Rapid Circle is growing rapidly and are therefore looking for the right person for the role. You will be given lots of freedom to develop personally. We also have a lot of in-house knowledge (MVPs) within the Netherlands, Australia, and India. By working closely with your (international) colleagues, you can continue to challenge yourself and create your own growth path. Freedom, entrepreneurship, and development are key at Rapid Circle, so also in the role of an Migration & Modernization Data Engineer.
Role Summary: A hands-on engineer who accelerates EDP consolidation by building reusable code, frameworks and migration artefacts to refactor data pipelines and data models into modern Lakehouse architecture. The role also guides business migration teams and applies AI/agentic automation to reduce migration effort, improve quality and speed up delivery.
| Core Responsibilities |
- Build reusable migration accelerators, templates, utilities, libraries and reference implementations for EDP onboarding.
- Refactor legacy data pipelines, data models and data products into scalable Lakehouse and Medallion architectures.
- Develop production-ready data pipelines using Databricks, Spark, Python/Scala, SQL and DBT.
- Define engineering patterns, standards and best practices for consistent migration and modernization delivery.
- Support data validation, reconciliation, testing, performance optimisation and operational readiness.
| Consulting & Advisory |
- Act as a technical consultant to business migration teams throughout assessment, planning and execution.
- Review current-state pipelines and data models, then recommend practical migration and refactoring approaches.
- Facilitate technical workshops, design reviews and migration planning discussions with business, architects and engineers.
- Help teams adopt EDP platform capabilities, governance, security and engineering standards.
| Technical Skills |
- Databricks: notebooks, workflows, jobs, Delta Lake, Unity Catalog and Lakehouse implementation.
- Apache Spark, Python/Scala and advanced SQL for scalable data engineering and optimisation.
- DBT for modelling, transformations, testing, documentation and deployment practices.
- Modern data architecture: ETL/ELT, batch/streaming, Medallion design, data products and enterprise data platforms.
- Data formats and modelling: Parquet, JSON, CSV, XML, dimensional modelling and analytics-ready structures.
| AI & Automation Skills |
- Ability to use GenAI and agentic AI to accelerate migration, refactoring, code conversion and documentation.
- Experience or strong understanding of building AI agents, copilots or automation assistants for engineering teams.
- Prompt engineering, AI-assisted development and workflow automation to improve delivery productivity.
- Ability to identify migration tasks that can be automated using AI, scripts, reusable tools or engineering frameworks.
| Preferred & Soft Skills |
- CI/CD, DevOps and Agile delivery experience in enterprise data engineering environments.
- Exposure to Power BI, self-service analytics, Data Mesh and data product management concepts.
- Strong stakeholder engagement, communication, documentation and problem-solving skills.
- Ability to manage competing priorities with a continuous learning mindset and strong ownership.
Company
Rapidcircle
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