[Remote] Big Data Engineer

Note: The job is a remote job and is open to candidates in USA. AdvanSix plays a critical role in global supply chains, innovating and delivering essential products for various end markets. They are seeking a Big Data Engineer to build and operate their enterprise Unified Data Layer, delivering data products that support multiple corporate functions and ensure trusted data governance.

Responsibilities

• Build ingestion pipelines (batch, CDC, streaming) from S/4HANA/DataSphere, PHD/historian, LIMS, TMS, HSE, and other sources into landing → curated → semantic layers
• Implement data contracts, schema/versioning, SCD handling, partitioning, and performance tuning (file formats, clustering, caching)
• Develop dimensional/semantic models that back certified Power BI datasets and APIs for apps/agents
• Integrate OT data via OPC UA/MQTT, broker/DMZ patterns, read-only historian feeds, and event/batch frames—no control-net reads
• Collaborate with plant controls on change control, signal quality, and downtime windows
• Embed data quality rules, unit/integration tests, and validation checks (freshness, completeness, drift/PSI)
• Instrument lineage and end-to-end monitoring; build alerting and on-call runbooks to minimize MTTR
• Enforce RBAC, secrets management, PII/HSE classifications, and retention aligned to Governance/MDM policies
• Automate build/test/deploy with Git-based CI/CD (environments, approvals, blue/green)
• Track and optimize cost/performance (cluster sizing, autoscaling, cache strategy); contribute to FinOps reviews
• Partner with Reporting & BI on semantic model contracts, RLS, and performance SLAs; avoid direct system scraping
• Produce “readme” docs, data dictionaries, runbooks, and post-incident reviews; support knowledge transfer with vendors

Skills

• 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
• 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

Benefits

• Paid holidays
• Paid time off including vacation
• Eligibility to purchase company stock
• Tuition reimbursement
• 401K with a competitive company match
• Discretionary financial benefits such as incentive pay, equity awards, and participation in a deferred compensation plan
• Medical, dental and vision insurance
• Flexible spending and health savings account eligibility
• Employer-provided short term disability benefits
• Eligibility to purchase long term disability benefits
• Employer-provided basic life insurance
• Eligibility to purchase voluntary life coverages

Company Overview

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