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Senior Data Engineer (Microsoft Fabric / Lakehouse)

We are seeking Data Engineers to architect and deliver a modern lakehouse data platform leveraging Microsoft Fabric.

This position blends hands-on development, solution design, and team leadership, playing a key role in both the initial platform build and its ongoing evolution.

Key Responsibilities:



Architecture & Design

  • Drive the implementation of a medallion architecture (Bronze, Silver, Gold)
  • Design scalable data models and reusable data products
  • Optimize the Gold layer for reporting, semantic models, and analytical workloads


Data Engineering (Hands-on)

  • Develop data transformation and enrichment logic using PySpark and SparkSQL
  • Build and maintain end-to-end data pipelines
  • Implement efficient incremental loading strategies (e.g. Delta merge, watermarking)
  • Refactor and modernize legacy ETL processes


Orchestration & Platform

  • Design and manage Fabric pipelines for scheduling and orchestration
  • Replace legacy orchestration tools such as SQL Agent or SSIS
  • Enable and support event-driven pipeline execution


Data Quality & Governance

  • Establish data validation, monitoring, and quality assurance processes
  • Ensure consistency, accuracy, and reliability across all data layers


DevOps & Best Practices

  • Implement CI/CD pipelines for data platform components
  • Promote Git-based version control and collaborative development workflows


Collaboration & Mentorship

  • Partner with stakeholders to translate business requirements into data solutions
  • Provide guidance and mentorship to junior engineers
  • Support testing, migration activities, and documentation efforts

Requirements:

  • 5-12 years of experience in data engineering or data platform development
  • Hands-on experience with Microsoft Fabric, Databricks, or Azure Synapse
  • Strong programming skills in Python / PySpark
  • Advanced SQL capabilities, including complex transformations and optimisation
  • Experience with Delta Lake (merge, partitioning, optimization)
  • Proven experience building data pipelines and orchestration frameworks
  • Solid understanding of dimensional modelling (e.g. star schema, SCD)

Nice to Have:

  • Experience with Fabric-specific tools (Lakehouses, Dataflows Gen2)
  • Knowledge of Power BI, semantic models, or DirectLake
  • Familiarity with Azure DevOps and CI/CD pipelines
  • Experience in data migration or modernisation initiatives
  • Exposure to data product or data mesh concepts