NOV
Overview
Design, develop, and optimize scalable, high-performance data pipelines to support analytics, condition-based maintenance, and drilling optimization KPIs. Build reliable ETL/ELT processes for structured and unstructured data from drilling rigs, rig sensors, and enterprise systems. Implement and monitor data quality checks to ensure integrity and reliability of equipment and operational data. Develop both streaming and batch ingestion pipelines for high-frequency sensor data and historical operational data. Enforce architecture, coding, and documentation standards for all supported platforms. Apply DevOps best practices to enable automated CI/CD, testing, and deployment for data engineering workflows. Partner with drilling engineers, reliability experts, and data scientists to integrate rig equipment data into predictive maintenance and optimization models. Collaborate with cross-functional teams to translate operational requirements into scalable data solutions. Proactively identify technology risks and propose solutions to ensure data availability and reliability in mission-critical systems.
Education
Bachelor’s or Master’s degree in Computer Science, Data Engineering, or related technical field. Certification in Databricks, cloud data engineering, or equivalent is preferred.
Technical Skills
4+ years of hands-on development experience in Python, PySpark, or another modern programming language. Advanced knowledge of data modeling techniques (normalization, dimensional modeling, entity-relationship). Expertise in designing and managing data pipelines across cloud and hybrid ecosystems (e.g., Databricks, SQL Server, Data Lakes, distributed systems, SQL/NoSQL databases). Proven experience with batch and real-time ETL pipelines for high-frequency telemetry or sensor data. Familiarity with CI/CD and DevOps tools (Git, JIRA, Confluence).
Domain Knowledge (Preferred but Highly Valued)
Experience with drilling and rig equipment data, including telemetry, SCADA, WITSML, or condition-based monitoring systems. Understanding of drilling optimization KPIs, rig operations, and equipment reliability concepts. Ability to bridge technical solutions with operational realities in oilfield environments.
Seniority level
Associate
Employment type
Full-time
Job function
Engineering and Information Technology
Industries
Oil and Gas
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Design, develop, and optimize scalable, high-performance data pipelines to support analytics, condition-based maintenance, and drilling optimization KPIs. Build reliable ETL/ELT processes for structured and unstructured data from drilling rigs, rig sensors, and enterprise systems. Implement and monitor data quality checks to ensure integrity and reliability of equipment and operational data. Develop both streaming and batch ingestion pipelines for high-frequency sensor data and historical operational data. Enforce architecture, coding, and documentation standards for all supported platforms. Apply DevOps best practices to enable automated CI/CD, testing, and deployment for data engineering workflows. Partner with drilling engineers, reliability experts, and data scientists to integrate rig equipment data into predictive maintenance and optimization models. Collaborate with cross-functional teams to translate operational requirements into scalable data solutions. Proactively identify technology risks and propose solutions to ensure data availability and reliability in mission-critical systems.
Education
Bachelor’s or Master’s degree in Computer Science, Data Engineering, or related technical field. Certification in Databricks, cloud data engineering, or equivalent is preferred.
Technical Skills
4+ years of hands-on development experience in Python, PySpark, or another modern programming language. Advanced knowledge of data modeling techniques (normalization, dimensional modeling, entity-relationship). Expertise in designing and managing data pipelines across cloud and hybrid ecosystems (e.g., Databricks, SQL Server, Data Lakes, distributed systems, SQL/NoSQL databases). Proven experience with batch and real-time ETL pipelines for high-frequency telemetry or sensor data. Familiarity with CI/CD and DevOps tools (Git, JIRA, Confluence).
Domain Knowledge (Preferred but Highly Valued)
Experience with drilling and rig equipment data, including telemetry, SCADA, WITSML, or condition-based monitoring systems. Understanding of drilling optimization KPIs, rig operations, and equipment reliability concepts. Ability to bridge technical solutions with operational realities in oilfield environments.
Seniority level
Associate
Employment type
Full-time
Job function
Engineering and Information Technology
Industries
Oil and Gas
#J-18808-Ljbffr