Senior Data Engineer (Microsoft Fabric)

About the role

Joblogic, a global field service management software company, is scaling its data department and needs a senior engineer who keeps the data running reliably today and architects the enterprise data warehouse for tomorrow. The role owns and hardens the current Azure-based ingestion and transformation pipelines, then designs and implements the data warehouse / lakehouse and leads the migration to Microsoft Fabric (or Databricks). It is hands-on and leadership-focused: setting engineering standards, mentoring two data engineers and owning the engineering branch.

Key responsibilities

• Own and maintain the ingestion pipelines feeding Marketing, Sales, CSM and Finance into the data lake, with consistent, auditable ingestion.
• Design, build and optimise ETL/ELT pipelines in Azure Data Factory, and write and tune complex SQL and stored procedures.
• Build Python automation and REST API integrations for external and third-party data.
• Enforce data quality, validation and lineage across every pipeline, and partner with the Analytics team so clean, modelled data feeds Power BI on time.
• Set the engineering bar (Git, code review, CI/CD) and mentor the two engineers.
• Monitor pipeline performance and cost, tuning compute and storage.
• Architect and implement the enterprise warehouse / lakehouse end-to-end, with medallion layers, dimensional models, canonical definitions and a governed semantic layer.
• Lead the migration to Microsoft Fabric (OneLake, Lakehouse & Warehouse, Data Factory, Direct Lake for Power BI) or Databricks, including phased cutover and legacy decommissioning.
• Define modelling, naming, partitioning and indexing standards, performance SLAs, and governance, security, lineage and cost controls.

Required profile

• Proven, hands-on experience designing and implementing a data warehouse or lakehouse from scratch, with modelling decisions and outcomes you can point to.
• 6+ years in data engineering, including senior ownership of architecture and delivery on at least one end-to-end warehouse or lakehouse build.
• Strong advantage: hands-on experience with Microsoft Fabric, or having led a migration to Fabric or Databricks; candidates with deep lakehouse experience on Databricks or Synapse who can pick it up fast are also invited to apply.
• Technical leadership of the engineering function, mentoring and raising the standard of the two engineers on the team.

Required skills

• Python for data engineering, automation and API work.
• SQL, including performance optimisation and stored procedures.
• Azure Data Factory, Azure SQL Database, Azure Blob and Data Lake storage, Azure Functions.
• Data modelling (dimensional / star schema), ETL/ELT, data validation and quality, database design.
• Git, REST API integration, performance optimisation and scalability.
• Near-required: Microsoft Fabric (OneLake, Lakehouse & Warehouse, Data Factory, Direct Lake for Power BI).
• Good to have: Apache Spark / Databricks, Docker, CI/CD pipelines, Azure DevOps, Power BI semantic models, FastAPI / Flask, event-driven architectures, Service Bus, Kafka, RabbitMQ, Purview, Agile / Scrum.