Principal Specialist, Corporate Functions Data Domain
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Job Purpose:
The Lead Specialist, Data Engineering is responsible for designing, developing, and optimizing scalable data engineering solutions across both OT (Operational Technology) and IT environments. The role ensures that data products, enterprise data layers, pipelines, and integration flows are consistent, governed, high-performing, and aligned with enterprise architecture.
This position operates as a senior technical specialist providing guidance across multidisciplinary engineering teams and ensuring cohesive OTāIT data ingestion, transformation, and consumption patterns.
Key Accountabilities:
- Design, build, and optimize ingestion, transformation, and orchestration pipelines across OT and IT data sources.
- implement scalable ELT/ETL workflows supporting enterprise analytics, data products, AI/ML, and operational use cases.
- Engineer unified data flows across remote mining sites, disconnected OT environments, manufacturing systems, edge computing devices, and IT cloud platforms.
- Embed metadata capture, lineage tracking, and quality checks into data pipelines to support data governance and cataloging requirements.
- Translate architectural models into physical engineering implementations.
- Partner with business domains to understand data requirements and ensure delivered pipelines meet operational and analytical needs.
- Address OT-specific latency, connectivity, protocol variability, and historian/SCADA integration considerations in pipeline designs.
Minimum Qualifications:
ļ· Bachelorās degree in Computer Science/Eng, Data Engineering, Information Systems, or related field.
ā¢
ļ· Masterās degree preferred (Data Architecture, Software Engineering, or AI/Analytics).
Minimum Experience:
ļ· 8+ years of hands-on experience in data engineering across modern architectures (cloud, data lake and warehouse, OT/IT).
ļ· Strong experience building data pipelines integrating OT systems (SCADA, DCS, historians) and IT data sources, ERP Fusion.
ļ· Practical experience with Azure, modern data lakehouse patterns, virtualization , and workflow orchestration.
ļ· Exposure to DevOps pipelines, containerization, data quality, and metadata management systems.
Maaden High-Performance Competencies:
ļ· Execution Excellence: Delivers high-quality pipelines and engineering solutions with strong reliability.
ļ· Collaboration & Influence: Works effectively across OT, IT, and business domains.
ļ· Problem Solving: Tackles complex integration challenges across industrial and corporate environments.
ļ· Adaptability & Innovation: Applies modern engineering techniques and identifies improvements in architecture/tooling.
ļ· Technical Leadership: Guides engineering teams and junior specialists.
Skills:
ļ· Advanced ELT/ETL development (e.g., Data Factory, Informatica, custom pipelines).
ļ· Strong programming in Python, SQL, and data transformation frameworks.
ļ· Experience with timeseries, historian, and sensor data coming from OT.
ļ· Deep understanding of streaming pipelines, micro-batching, and realtime architectures.
ļ· Strong knowledge of cloud platforms (Azure preferred), data lakehouse, Delta/Parquet formats, API integration, and orchestration tools.
ļ· Familiarity with DevOps practices, CI/CD, and Git-based workflows.
Requirements
- ā¢Bachelorās degree in Computer Science/Eng, Data Engineering, Information Systems, or related field
- ā¢Masterās degree preferred (Data Architecture, Software Engineering, or AI/Analytics)
- ā¢8+ years of hands-on experience in data engineering across modern architectures (cloud, data lake and warehouse, OT/IT)
- ā¢Strong experience building data pipelines integrating OT systems (SCADA, DCS, historians) and IT data sources, ERP Fusion
- ā¢Practical experience with Azure, modern data lakehouse patterns, virtualization, and workflow orchestration
- ā¢Exposure to DevOps pipelines, containerization, data quality, and metadata management systems
Nice to Have
- ā¢Advanced ELT/ETL development (e.g., Data Factory, Informatica, custom pipelines)
- ā¢Strong programming in Python, SQL, and data transformation frameworks
- ā¢Experience with timeseries, historian, and sensor data coming from OT
- ā¢Deep understanding of streaming pipelines, micro-batching, and realti
Responsibilities
- ā¢Design, build, and optimize ingestion, transformation, and orchestration pipelines across OT and IT data sources
- ā¢Implement scalable ELT/ETL workflows supporting enterprise analytics, data products, AI/ML, and operational use cases
- ā¢Engineer unified data flows across remote mining sites, disconnected OT environments, manufacturing systems, edge computing devices, and IT cloud platforms
- ā¢Embed metadata capture, lineage tracking, and quality checks into data pipelines to support data governance and cataloging requirements
- ā¢Translate architectural models into physical engineering implementations
- ā¢Partner with business domains to understand data requirements and ensure delivered pipelines meet operational and analytical needs
- ā¢Address OT-specific latency, connectivity, protocol variability, and historian/SCADA integration considerations in pipeline designs
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- See if your CV survives Ma'aden's ATS filters
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- Download Gulf-ready CV
60 seconds. $3.99 one-time.
Ma'aden is a Saudi Arabian mining and metals company developing the country's mineral resources. They focus on producing aluminum, gold, phosphates, and other industrial minerals.
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