Come join us
In the Data Engineer role, you’ll expand your expertise by contributing to modern initiatives across a variety of industries and business domains. You’ll work with a broad toolset, with responsibilities including:
What you’ll do
- Creating, developing, and operating scalable, efficient, and dependable data pipelines
- Delivering end-to-end data platforms, including data architecture and ETL implementations
- Partnering with data scientists, analysts, and engineering teams to integrate data and improve end-to-end performance
- Applying best practices for data governance, quality, and security across the data estate
- Tuning and streamlining data workflows to maximize reliability and throughput
- Keeping current with new trends and advancements in data engineering
- Supporting and coaching junior data engineers through mentoring and knowledge sharing
- Opportunity to grow your skills in advanced AI technologies
Tech stack
You’ll use a range of tools depending on the project, however our core stack typically includes:
Databricks, PySpark, Azure cloud and services (Data Lake, SQL Database, Azure Databricks, Azure Data Factory), SQL, Python, MS Fabric
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Skills and experiences :
Must-have skills
To be successful in this position, you should have hands-on commercial experience with:
- Azure cloud and services (e.g. Azure Data Factory, Data Lake, SQL Database, Azure Databricks)
- Databricks (commercial project experience)
- Python and PySpark for building and operating data solutions
- SQL for querying, transforming, and validating data
- Core data engineering practices (ETL, data modeling, data warehousing, data governance)
- English at B2 level (or higher)
Nice to have:
- Hands-on experience with MS Fabric
- Familiarity with containerization and orchestration (Docker/Kubernetes)
- Understanding of machine learning concepts and frameworks (e.g. MLflow, TensorFlow)
- Knowledge or experience with LLMs and orchestration frameworks
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