Assignment Description

We are seeking a Data Product & Platform Operations Engineer to build and operate end-to-end Microsoft Fabric data products, from ingestion and layered transformation to modelling and publication. The role includes creating reusable, metadata-driven delivery patterns and implementing data contracts, governance standards, lifecycle controls and ownership information.

You will support domain data products and Gold-layer preparation, manage cataloguing, lineage, classification and data quality, and define validation, certification and operational controls. You will also maintain dashboards for platform health, reliability, refresh status, usage, incidents and cost, while managing SLAs, SLOs, incident routines, runbooks, support processes, continuous improvement and day-to-day FinOps activities, including capacity monitoring, cost allocation, showback, anomaly detection and optimisation recommendations.

The assignment includes onboarding domain teams to platform standards and ways of working. You must work across the analytics function and the data platform function, with part of the assignment allocated to a secondary team as priorities require. You should be comfortable working in an environment where not everything is fully defined and routinely create clear documentation, reusable patterns and knowledge-sharing practices. The role also requires effective collaboration with technical and business stakeholders, transparent work with backlogs, priorities, delivery plans and agile methods, clear English communication and active efforts to reduce dependency on individual team members.

Required Qualifications:

• Strong ability to script and automate technical processes.
• Around five years or more of relevant experience in data engineering, with exposure to governance or operational responsibilities.
• Experience with monitoring, operational reporting, troubleshooting and platform support.
• Practical experience applying governance measures related to metadata, data quality, catalog tools, documentation and operational controls.
• Ability to collaborate across technical functions, governance roles and business stakeholders, with strong documentation discipline.
• Experience creating reusable data products and pipelines with frameworks and templates rather than relying solely on one-off implementations.
• Strong practical data engineering skills in PySpark or Spark, Python, SQL, pipeline orchestration and incremental-loading approaches.
• Practical experience with Microsoft Fabric, or strong experience with Databricks or Synapse and a clear path for transferring that knowledge to Fabric, including Lakehouse, notebooks, pipelines and OneLake or comparable concepts.

It is considered advantageous if you have experience with Microsoft Purview, including cataloguing, lineage, Data Map and data-quality capabilities; Fabric operations, including the Capacity Metrics App, Monitoring Hub, workspace monitoring and usage reporting; data-quality tools such as Great Expectations, dbt tests or equivalent; FinOps or cloud cost management and relevant certification; SLA and SLO tracking, incident management and platform-support processes; data contracts, domain-owned data products and data-product lifecycle management; CI/CD and automated testing for data pipelines; CDC and event-driven ingestion; or a relevant certification such as DP-700.