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Lead – Data Ops

Lead – Data Ops

Reliance Bio Energynavi mumbai, India
18 hours ago
Job description

Job Purpose :

To lead the development and management of robust data infrastructure and pipelines across the CBG network, enabling the delivery of data as a product. This role ensures high-quality, accessible, and timely data is available for advanced analytics, reporting, and decision-making across all operational and business functions.

Key Responsibilities :

Data Infrastructure Development :

  • Design, implement, and manage scalable data architecture for collecting, storing, and processing large volumes of data from CBG plant systems (SCADA, PLC, IoT devices, SAP, EMS, LIMS, etc.).
  • Own the cloud / on-prem data lake, data warehouse, and structured databases supporting both real-time and batch processing.

Pipeline Engineering & Orchestration :

  • Develop and maintain robust, automated data pipelines using modern ETL / ELT tools
  • Ensure reliability, efficiency, and monitoring of all data flows from source to destination systems.

    • Data Quality & Governance :

  • Implement processes to ensure data accuracy, consistency, completeness, and freshness.
  • Work with Data Governance and Compliance teams to define standards, validation rules, and audit trails.

    • Cross-Functional Collaboration :

  • Collaborate with data scientists, business analysts, application teams, and plant operations to understand and prioritize data requirements.
  • Enable self-service data access through APIs, secure dashboards, and curated datasets.

    • Metadata & Cataloguing :

  • Maintain a data catalogue and lineage tracking system to improve data discoverability and reusability across the organization.
  • Provide documentation and training on data schema, usage, and access policies.

    • Security & Compliance :

  • Ensure data is stored and accessed securely, following best practices in encryption, role-based access, and regulatory compliance.

    • Key Skills :

  • B.E. / B.Tech
  • Expertise in SQL, Python, DevOps and distributed data technologies (e.g., Spark, Kafka).
  • Experience with cloud platforms such as AWS, Azure, or GCP, and associated data services Strong understanding of CI / CD for data pipelines and MLOps integration.
  • Familiarity with industrial data sources (OPC-UA, MQTT, SCADA systems) is highly desirable.
  • Excellent leadership, documentation, and stakeholder communication skills.
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