Big Data Engineer

🕒 4 days ago

⚔️ Virginia – Remote

⚔️ Virginia – Remote

💵 $104.6k - $156.8k / year

⏰ Full Time

🟡 Mid-level

🟠 Senior

🚰 Data Engineer

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AdvanSix

WebsiteLinkedInAll Job Openings

1001 - 5000 employees

Founded 2016

🏭 Manufacturing

🤝 B2B

💰 $12M Grant - AdvanSix on 2024-09

Manufacturing • B2B

AdvanSix is a U. S. -based chemical manufacturer that produces nylon 6, caprolactam, ammonium sulfate and other chemical intermediates and performance materials for industrial customers. The company operates integrated chemical production facilities supplying polymers, fibers and specialty chemicals to customers in plastics, textiles, agriculture (fertilizers) and other industrial markets. AdvanSix primarily serves business customers (B2B) and focuses on large-scale manufacturing and materials production.

📋 Description

• AdvanSix is seeking a Big Data Engineer to build and operate our enterprise Unified Data Layer (UDL). • Engineer batch/CDC/streaming pipelines, model curated/semantic layers, and harden run-state with testing, CI/CD, security, and observability. • Partner closely with the data team and larger IT organization. • Design and deliver scalable, secure data pipelines and data models that safely connect operational systems to analytics. • Build ingestion pipelines (batch, CDC, streaming) from S/4HANA/DataSphere, PHD/historian, LIMS, TMS, HSE, and other sources. • Implement data contracts, schema/versioning, SCD handling, partitioning, and performance tuning. • Develop dimensional/semantic models that back certified Power BI datasets and APIs for apps/agents. • Integrate OT data via OPC UA/MQTT and collaborate with plant controls on change control, signal quality, and downtime windows. • Embed data quality rules, unit/integration tests, and validation checks. • Automate build/test/deploy with Git-based CI/CD.

🎯 Requirements

• 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. • Strong SQL and Python/PySpark; comfort with Spark Structured Streaming and performance tuning. • Experience implementing tests/observability (freshness, schema, expectations), and Git-based CI/CD. • Familiarity with SAP S/4HANA structures and SAP DataSphere semantic modeling. • OT concepts: historians (PHD/PI), OPC UA/MQTT, event/batch frames, ISA-95/99 basics. • Understanding of Power BI consumption (semantic models, RLS) and APIs for downstream AI/ML apps/agents.