Big Data Engineer

Kforce has a client that is seeking a Big Data Engineer in Parsippany, NJ. Summary: This role is responsible for designing and building enterprise-scale data pipelines that ingest information from business systems, operational technology environments, and industrial data sources into a unified analytics platform. The position develops and optimizes data models, semantic layers, and curated datasets that support reporting, APIs, AI, and advanced analytics. The Engineer works closely with the plant and controls teams to securely integrate OT data using industry-standard architectures while ensuring production systems remain protected. A key focus is maintaining high data quality, security, governance, monitoring, and reliability through testing, observability, lineage tracking, and access controls. The role also drives CI/CD automation, performance optimization, and cloud cost management to ensure scalable and efficient data platform operations.

• Minimum 5 years in data engineering building production pipelines at scale (batch/CDC/streaming)
• Hands-on with Azure data stack: Databricks or Fabric/Synapse, ADF/Pipelines, ADLS/OneLake, Azure SQL/SQL MI, Key Vault
• Experience implementing tests/observability (freshness, schema, expectations), and Git-based CI/CD
• Familiarity with SAP S/4HANA structures and SAP DataSphere semantic modeling
• Understanding of Power BI consumption (semantic models, RLS) and APIs for downstream AI/ML apps/agents
• Strong SQL and Python/PySpark; comfort with Spark Structured Streaming and performance tuning
• OT concepts: historians (PHD/PI), OPC UA/MQTT, event/batch frames, ISA-95/99 basics

• Time-series/data-quality tooling (e.g., Great Expectations or equivalent patterns), feature/metric stores
• MDM concepts (keys, survivorship), lineage/catalog tooling
• TMS/WMS, LIMS, Historian, HSE domain exposure; Lean/Six Sigma mindset; FinOps awareness