Summary
✨ AI‑Generated
Join a data engineering team working across diverse industries and modern technology initiatives. You will design and operate scalable data pipelines, deliver end-to-end data platforms and ETL solutions, collaborate with data scientists and analysts, improve governance and quality, optimize workflows, and help advance AI capabilities.
Highlights
Broad exposure to modern data initiatives across multiple industries and business domains. The role provides opportunities to expand technical expertise, work with diverse tools, contribute to AI initiatives, and mentor junior data engineers.
Description
Come join us
What You’ll Do
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:
Creating, developing, and operating scalable, efficient, and dependable data pipelinesDelivering end-to-end data platforms, including data architecture and ETL implementationsPartnering with data scientists, analysts, and engineering teams to integrate data and improve end-to-end performanceApplying best practices for data governance, quality, and security across the data estateTuning and streamlining data workflows to maximize reliability and throughputKeeping current with new trends and advancements in data engineeringSupporting and coaching junior data engineers through mentoring and knowledge sharingOpportunity 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
Qualifications
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 solutionsSQL for querying, transforming, and validating dataCore data engineering practices (ETL, data modeling, data warehousing, data governance)English at B2 level (or higher)
Nice To Have
Hands-on experience with MS FabricFamiliarity 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
