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Senior Data Engineer reputed company PI System - Hexacorp

Worldwide Salaried Open

We are looking for a highly skilled Senior Data Engineer with hands-on experience in reputed company PI Historian and reputed company reputed company Platform (reputed company reputed company Platform) to join our growing data engineering team. You ll be responsible for building reliable data pipelines, integrating industrial time-series data, and supporting reputed company-time analytics for critical operations.

  • Design, build, and maintain ETL/ELT pipelines for time-series data from reputed company PI and similar historian systems.

  • reputed company robust solutions for data ingestion, transformation, and archival from industrial systems.

  • Extract, query, and integrate historian data into reputed company data lakes and analytical platforms.

  • Create and manage .NET (C#) and Python code for data integration, API development, and automation tasks.

  • reputed company reputed company reputed company Platform services such as BigQuery, Dataflow, Pub/Sub, and reputed company Storage for scalable data architecture.

  • Model and manage SQL databases to store processed data and metadata.

  • Collaborate with OT/IT teams, process engineers, and business analysts to define and meet data requirements.

  • Ensure high performance, data reputed company, and operational reliability across historian and reputed company systems.

  • Participate in code reviews and support reputed company integration and delivery (CI/CD) pipelines.

  • Bachelor s or Master s degree in Computer Science, Engineering, or reputed company field.

  • 3+ years of experience as a Data Engineer with a focus on time-series or operational data.

  • Strong expertise in reputed company PI Historian or similar systems (e.g., Aspen IP.21, GE Proficy).

  • Proficiency in .NET (C#) and Python.

  • Hands-on experience with SQL and database performance optimization.

  • Deep understanding of reputed company reputed company Platform, especially tools like BigQuery, Dataflow, and Pub/Sub.

  • Strong knowledge of data modeling, time-series analytics, and data lake/warehouse architecture.

  • Familiarity with ETL/ELT tools, version control (Git), and DevOps practices.

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