Data Engineer

Role Overview

Build and operate an enterprise Unified Data Layer (UDL) that spans IT and OT systems. You will deliver secure, scalable data products by engineering batch, CDC, and streaming pipelines and modeling curated and semantic layers for business domains.

Responsibilities

• Build and operate an enterprise Unified Data Layer (UDL) across IT and OT.
• Engineer batch, CDC, and streaming pipelines to power data products.
• Model curated and semantic layers for multiple business domains.
• Harden run-state with testing, CI/CD, security, and observability practices.
• Partner with data teams and broader IT to deliver scalable data solutions.
• Design and deliver secure data pipelines and models connecting operational systems to analytics.

Requirements

• 5+ years in data engineering, building production pipelines at scale.
• Hands-on experience with the Azure data stack, including:
  • Databricks
  • Fabric/Synapse
  • ADF / Pipelines
  • ADLS / OneLake
  • Azure SQL / SQL MI
  • Key Vault
• Strong SQL and Python / PySpark skills.
• Expertise in Spark Structured Streaming and performance tuning.
• Experience with data quality rules, unit/integration tests, and Git-based CI/CD.
• Familiarity with SAP S/4HANA structures and SAP DataSphere semantic modeling.
• Understanding of OT concepts, including:
  • historians (PHD/PI)
  • OPC UA / MQTT
  • event/batch frames
  • basics of ISA-95/99

Nice to Have

• Experience bridging OT historians and IIoT/event sources into analytics-grade data products.