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 OT–IT data ingestion, transformation, and consumption patterns.
Key Accountabilities:
Minimum Qualifications:
Bachelor’s degree in Computer Science/Eng, Data Engineering, Information Systems, or related field.
Master’s degree preferred (Data Architecture, Software Engineering, or AI/Analytics).
Minimum Experience:
8+ years of hands-on experience in data engineering across modern architectures (cloud, data lake 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:
Execution Excellence: Delivers high-quality pipelines and engineering solutions with strong reliability.
Collaboration & Influence: Works effectively across OT, IT, and business domains.
Problem Solving: Tackles complex integration challenges across industrial and corporate environments.
Adaptability & Innovation: Applies modern engineering techniques and identifies improvements in architecture/tooling.
Technical Leadership: Guides engineering teams and junior specialists.
Skills:
Advanced ELT/ETL development (e.g., Data Factory, Informatica, custom pipelines).
Strong programming in Python, SQL, and data transformation frameworks.
Experience with timeseries, historian, and sensor data coming from OT.
Deep understanding of streaming pipelines, micro-batching, and realtime architectures.
Strong knowledge of cloud platforms (Azure preferred), data lakehouse, Delta/Parquet formats, API integration, and orchestration tools.
Familiarity with DevOps practices, CI/CD, and Git-based workflows.
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