Principal Specialist, Engineering and ETL (OT)
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Job Purpose
The Principal Specialist, Engineering and ETL (OT) provides enterprise leadership for OT data engineering, enabling reliable ingestion, transformation, and availability of operational data for analytics, operations, and performance management. The role defines OT pipeline standards and assures that OT data is delivered with quality, lineage, security, and appropriate latency across sites.
This position is responsible for defining scalable patterns for integrating historians and industrial systems into enterprise platforms, guiding teams through complex OT constraints, and ensuring operational data products are sustainable and governed.
Key Accountabilities
• Define OT data engineering and ETL standards, patterns, and reference architectures covering batch, streaming, and near-real-time ingestion needs.
• Establish ingestion patterns for historians and OT source systems, including normalization, unit standardization, quality flags, and tag mapping processes.
• Design and assure robust pipeline reliability (idempotency, backfill, late-arriving data handling, reconciliation, alerting) appropriate for OT contexts.
• Ensure OT pipelines comply with security and segmentation requirements; partner with OT cyber and platform security teams for governance-by-design.
• Oversee and guide OT data transformation logic to produce curated OT data products aligned to enterprise models and governance requirements.
• Provide architectural oversight for site onboarding, handling variability across plants and ensuring consistent delivery standards across implementations.
• Review and assure vendor and internal deliverables; provide technical direction and quality gates for complex OT engineering initiatives.
• Drive continuous improvement through performance tuning, cost optimization, observability, and operational resilience improvements for OT workloads.Minimum Qualification, Experience and Competencies
Minimum Qualification
• Bachelor’s degree in Computer Science/Engineering, Data Engineering, Industrial Engineering, or related field.
• Master’s degree preferred; OT systems exposure is an advantage.
Minimum Experience
• 10–15 years of experience in data engineering/ETL with demonstrated exposure to OT/industrial data environments.
• Experience designing ingestion from historians/OT systems and delivering analytics-ready OT datasets at enterprise scale.Skills:
• Strong OT data engineering expertise including ingestion from historians, handling time-series characteristics, and ensuring data quality.
• Ability to design scalable, secure OT-to-IT data pipelines with governance, lineage, and auditability.
• Advanced pipeline engineering practices (reliability, observability, orchestration, performance tuning).
• Stakeholder leadership across plant operations, OT engineering, IT, and analytics consumers.
• Vendor assurance and technical governance for complex multi-site delivery programs.
Requirements
- •Bachelor's degree in Computer Science/Engineering, Data Engineering, Industrial Engineering, or related field
- •10–15 years of experience in data engineering/ETL with demonstrated exposure to OT/industrial data environments
- •Experience designing ingestion from historians/OT systems and delivering analytics-ready OT datasets at enterprise scale
- •Strong OT data engineering expertise
- •Ability to design scalable, secure OT-to-IT data pipelines with governance, lineage, and auditability
- •Advanced pipeline engineering practices
- •Stakeholder leadership across plant operations, OT engineering, IT, and analytics consumers
- •Vendor assurance and technical governance for complex multi-site delivery programs
Nice to Have
- •Master's degree preferred
- •OT systems exposure is an advantage
Responsibilities
- •Define OT data engineering and ETL standards, patterns, and reference architectures
- •Establish ingestion patterns for historians and OT source systems
- •Design and assure robust pipeline reliability
- •Ensure OT pipelines comply with security and segmentation requirements
- •Oversee and guide OT data transformation logic
- •Provide architectural oversight for site onboarding
- •Review and assure vendor and internal deliverables
- •Drive continuous improvement through performance tuning, cost optimization, observability, and operational resilience
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