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Big Data Engineer
Location
United States
Posted
78 days ago
Salary
$104.6K - $156.8K / year
Seniority
Mid Level
Job Description
Big Data Engineer
AdvanSix
Role Description AdvanSix is seeking a Big Data Engineer to build and operate our enterprise Unified Data Layer (UDL) - spanning IT and OT - to deliver trustworthy, performant data products that power Finance, Operations, Supply Chain & Logistics, HSE, Commercial, and corporate analytics. You’ll engineer batch/CDC/streaming pipelines, model curated/semantic layers, and harden run-state with testing, CI/CD, security, and observability. You’ll partner closely with the data team and larger IT organization. Mission - Design and deliver scalable, secure data pipelines and data models that safely connect operational systems to analytics. - Ensure trusted and well‑governed data. - Enable repeatable delivery of BI, ML, AI, and automation solutions. Data Engineering & Modeling - 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. OT/IT Integration & Safety - 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. Quality, Security & Observability - 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. CI/CD, Cost & Reliability - 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. Collaboration & Documentation - 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. Qualifications - 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. Preferred Qualifications - 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 - We provide benefits that are industry competitive and focused on employee well-being. - Total Rewards program includes a competitive compensation, health, dental, vision & wellness programs, paid vacation, 401K with company matching, health savings programs, disability & life insurance, employee assistance program. - Tuition reimbursement for continued education, certifications, training, and development. - Work within a fast paced and innovative company, meeting passionate colleagues and partners with diverse backgrounds and experiences.
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