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Data Engineer (OT Data) (Category - Engineer) Sector: Oil and Gas Location: Doha, Qatar Experience - 10 years About Us At Codvo, we are committed to building scalable, future-ready data platforms that power business impact. We believe in a culture of innovation, collaboration, and growth, where engineers can experiment, learn, and thrive. Join us to be part of a team that solves complex data challenges with creativity and cutting-edge technology. The Opportunity: The Data Engineer will be a foundational architect of our delivery strategy, responsible for building and maintaining the data ecosystem required for our scoped-out use cases. You will be the crucial link between our vast, complex data sources and our advanced analytics ambitions. This involves tackling the unique challenges of the oil and gas sector, bridging the worlds of operational technology (OT)—with its real-time drilling data, SCADA systems, and seismic surveys—and information technology (IT). Your mission is to build the specific, high-performance data pipelines required to deliver our portfolio of projects. This means going beyond simple data movement; you will be creating reliable, scalable, and secure data products that serve as the fuel for our most critical AI models and analytics dashboards, directly enabling tangible business value and competitive advantage.
Job Responsibility
Architect & Build Data Pipelines: Design, construct, install, test, and maintain highly scalable data management systems and ETL/ELT pipelines
Integrate Diverse Data Sources: Develop processes to ingest and integrate high-volume, high-velocity data from SCADA systems, historians (like OSIsoft PI, Aspen InfoPlus.21), DCS, PLC, and IoT sensors
Cloud Data Platform Development: Implement and manage data solutions on the Microsoft Azure cloud platform, Leveraging services like Azure IoT Hub, Azure Event Hubs, and Azure Stream Analytics for real-time ingestion and processing of operational technology (OT) data
Data Modelling & Warehousing: Design and implement data models optimized for time-series data from industrial assets, supporting operational dashboards and real-time analytics
Enable Advanced AI: Build the data infrastructure to support AI/ML models for predictive maintenance, operational anomaly detection, and process optimization using real-time OT data
Champion Master Data Management (MDM): Design and implement MDM strategies and solutions to create a single, authoritative source of truth for critical data domains such as wells, equipment, and assets, ensuring data consistency across the enterprise
Ensure Data Quality & Governance: Implement robust data quality checks, validation rules, and monitoring to ensure the accuracy, consistency, and reliability of our data. Adhere to and help shape our data governance policies
Embrace Industry Standards: Champion and implement industry-specific data standards and models, such as the OSDU™ Data Platform, to ensure interoperability and a unified data view across the upstream lifecycle
Collaborate & Innovate: Work closely with a cross-functional team of geoscientists, drilling engineers, data scientists, and business analysts to understand their data needs and deliver effective solutions
Automate & Optimize: Identify opportunities for process automation and infrastructure optimization to improve data delivery, scalability, and cost-effectiveness
Security First: Implement and maintain security best practices to protect our sensitive and proprietary data assets
Requirements
Bachelor's in engineering, Information Systems, or a related quantitative field
5+ years of proven experience in a data engineering role
Experience within oil and gas industry is highly preferred
Demonstrable experience building and operationalizing large-scale data pipelines and applications
Nice to have
Familiarity with historian systems (e.g., OSIsoft PI System) and their data structures
Hands-on experience with the OSDU™ Data Platform
Experience working with industrial communication protocols (e.g., OPC UA, Modbus TCP/IP)
Understanding of cybersecurity considerations for OT environments and data segregation
Experience integrating data from ERP systems like SAP
Professional certifications in Azure or Databricks
Advanced SQL skills, including query optimization and performance tuning
Knowledge of containerization technologies (Docker, Kubernetes)
Experience of constructing and maintaining enterprise knowledge graphs