
Lead Specialist, Integrated Data, AI & Analytics Platform II
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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
Support Enterprise Architecture Direction
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Design, build, and optimize ingestion, transformation, and orchestration pipelines across OT and IT data sources.
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Implement scalable ELT/ETL workflows supporting enterprise analytics, data products, AI/ML, and operational use cases.
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Engineer unified data flows across remote mining sites, disconnected OT environments, manufacturing systems, edge computing devices, and IT cloud platforms.
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Embed metadata capture, lineage tracking, and quality checks into data pipelines to support data governance and cataloging requirements.
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Translate architectural models into physical engineering implementations.
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Partner with business domains to understand data requirements and ensure delivered pipelines meet operational and analytical needs.
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Address OT-specific latency, connectivity, protocol variability, and historian/SCADA integration considerations in pipeline designs.
Minimum Qualification, Experience and Competencies
Minimum Qualification
⢠Bachelorās degree in Computer Science/Eng, Data Engineering, Information Systems, or related field.
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Masterās degree preferred (Data Architecture, Software Engineering, or AI/Analytics).
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Minimum Experience
⢠8+ years of hands-on experience in data engineering across modern architectures (cloud, data laken and warehouse, OT/IT).
⢠Strong experience building data pipelines integrating OT systems (SCADA, DCS, historians) and IT data sources, ERP Fusion.
⢠Practical experience with Azure, modern data lakehouse patterns, virtualization , and workflow orchestration.
⢠Exposure to DevOps pipelines, containerization, data quality, and metadata management systems.
Maaden High Performance Competencies
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Execution Excellence: Delivers high-quality pipelines and engineering solutions with strong reliability.
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Collaboration & Influence: Works effectively across OT, IT, and business domains.
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Problem Solving: Tackles complex integration challenges across industrial and corporate environments.
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Adaptability & Innovation: Applies modern engineering techniques and identifies improvements in architecture/tooling.
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Technical Leadership: Guides engineering teams and junior specialists.
Skills
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Advanced ELT/ETL development (e.g., Data Factory, Informatica, custom pipelines).
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Strong programming in Python, SQL, and data transformation frameworks.
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Experience with time-series, historian, and sensor data coming from OT.
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Deep understanding of streaming pipelines, micro-batching, and real-time architectures.
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Strong knowledge of cloud platforms (Azure preferred), data lakehouse, Delta/Parquet formats, API integration, and orchestration tools.
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Familiarity with DevOps practices, CI/CD, and Git-based workflows
Requirements
- ā¢Design, build, and optimize ingestion, transformation, and orchestration pipelines
- ā¢Implement scalable ELT/ETL workflows
- ā¢Engineer unified data flows across remote mining sites, OT environments, manufacturing systems, edge devices, and IT cloud platforms
- ā¢Embed metadata capture, lineage tracking, and quality checks
- ā¢Translate architectural models into physical engineering implementations
- ā¢Partner with business domains to understand data requirements
- ā¢Address OT-specific latency, connectivity, protocol variability, and historian/SCADA integration considerations
- ā¢Bachelorās degree in Computer Science/Eng, Data Engineering, Information Systems, or related field
Nice to Have
- ā¢Masterās degree preferred (Data Architecture, Software Engineering, or AI/Analytics)
- ā¢Adaptability Innovation: Applies modern engineering techniques
- ā¢Technical Leadership: Guides engineering teams and junior specialists
- ā¢Strong programming in Python, SQL, and data transformation frameworks
- ā¢Experience with time-series, historian, and sensor data coming from OT
Responsibilities
- ā¢Support Enterprise Architecture Direction
- ā¢Minimum Experience: 8+ years of hands-on experience in data engineering
- 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
- ā¢Execution Excellence: Delivers high-quality pipelines and engineering solutions
- ā¢Collaboration Influence: Works effectively across OT, IT, and business domains
- ā¢Problem Solving: Tackles complex integration challenges
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