Data Product & Platform Operations Engineer

We are looking for a highly skilled Data Product & Platform Operations Engineer to join a large-scale data transformation environment focused on building and operating a modern self-service data platform. The team is responsible for enabling governed self-service analytics, scalable data products, operational excellence, and reporting solutions built on the Microsoft ecosystem.
You will primarily contribute to the Self-Service Data Platform (SSDP), while also supporting a Business Insights team where priorities require. This role combines hands-on data engineering, platform operations, governance implementation, observability, monitoring, and FinOps responsibilities.

Responsibilities

Data Product Engineering

• Build and operate data products on Microsoft Fabric from ingestion through consumption-ready layers.
• Develop Bronze, Silver, and Gold data layers.
• Implement scalable data models and publication processes.
• Create reusable frameworks, templates, notebook libraries, and parameterized pipelines.
• Enable metadata-driven ingestion and delivery patterns.

Data Governance & Quality

• Define and implement data contracts and metadata standards.
• Establish lifecycle controls and ownership frameworks.
• Implement lineage, cataloging, classification, and data quality capabilities.
• Create validation rules, quality checks, certification criteria, and operational controls.

Platform Operations & Observability

• Build operational dashboards for platform health and reliability.
• Monitor pipeline execution, refresh status, usage patterns, incidents, and costs.
• Define SLAs, SLOs, incident processes, support routines, and runbooks.
• Drive continuous improvement initiatives.

FinOps

• Manage platform cost visibility and optimization.
• Monitor capacity utilization and cost allocation.
• Perform anomaly detection and create optimization recommendations.
• Support showback and consumption reporting initiatives.

Stakeholder Collaboration

• Support onboarding of domain teams.
• Work closely with engineering, governance, and business stakeholders.
• Produce high-quality documentation and reusable standards.
• Reduce single-person dependency through knowledge sharing and transparency.

Required Skills & Experience

Must-Have

• Minimum 5+ years of Data Engineering experience.
• Strong hands-on experience with:
  • Microsoft Fabric
  • PySpark / Apache Spark
  • SQL
  • Python
  • Pipeline orchestration
  • Incremental loading patterns
• Experience building reusable data platforms, frameworks, and templates.
• Strong automation and scripting capabilities.
• Experience with monitoring, support, troubleshooting, and operational reporting.
• Governance implementation experience including metadata, cataloging, documentation, and data quality.
• Strong stakeholder management and documentation skills.

Preferred

• Microsoft Purview (Catalog, Data Map, Lineage, Data Quality).
• Fabric Capacity Metrics App, Monitoring Hub, workspace monitoring.
• CI/CD and automated testing for data platforms.
• Great Expectations, dbt tests, or equivalent quality tooling.
• CDC and event-driven ingestion.
• Data product lifecycle management and data contracts.
• FinOps experience and/or certification.
• DP-700 certification or similar.
  

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