Data Engineer

Are you passionate about leveraging data and analytics to drive operational impact in the energy sector? At NOV, we lead technological innovation to deliver exceptional value to our customers in drilling and rig equipment solutions. We are seeking a talented Data Engineer who not only excels at building scalable data architectures but also understands the unique challenges and opportunities within oilfield equipment and drilling operations.

In this role, you will design, develop, and support a robust data ecosystem that powers real-time insights for condition-based maintenance, drilling optimization, and operational efficiency. You will work closely with engineers, data scientists, and operational experts to translate business needs into technical solutions that enhance reliability and performance across NOV’s global operations. By joining our team, you’ll help transform how drilling and rig equipment data drives operational excellence. Your work will directly support predictive maintenance, drilling optimization, and operational safety, ensuring our customers can achieve maximum efficiency and uptime.

Responsibilities:

• 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.

Requirements:

• Bachelor’s or Master’s degree in Computer Science, Computer Engineering or Data Engineering.
• Minor in Mechanical Engineering is a plus.
• Certification in Databricks, cloud data engineering, or equivalent is preferred.
• 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).
• 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.