Data Engineer

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:

• Collaborate with drilling engineers, reliability experts, and data scientists to turn business problems into technical solutions.
• Design, develop, and operationalize data pipelines and analytics to support NOV’s drilling optimization and condition-based maintenance programs.
• Prepare, transform, and validate structured and unstructured operational data and high-frequency sensor data for analytics.
• Productionize and deploy data pipelines and analytical models in cloud and hybrid environments.
• Build and support automated testing, CI/CD workflows, and deployment pipelines.
• Implement data quality validation and monitoring.
• Adhere to and maintain architecture, coding, and documentation standards.
• Proactively identify technology risks and propose solutions to ensure data availability and reliability in mission-critical systems.

Required:

• Bachelor’s or Master’s degree in Computer Science, Computer Engineering, Data Engineering, or related field.
• 4+ years of hands-on development experience in Python or another modern programming language.
• Strong SQL skills and experience with modern data platforms and technologies (e.g., Databricks, SQL Server, SQL/NoSQL databases).
• Strong understanding of relational database design, normalization, and dimensional data modeling.
• Experience building and maintaining batch and streaming ELT/ETL pipelines.
• Experience preparing, transforming, and cleaning data for analytics or machine learning applications.
• Experience with cloud platforms (AWS preferred).
• Experience with Git, automated testing, CI/CD workflows, and deployment automation.
• Familiarity with containerization technologies (e.g., Docker).
• Familiarity with Agile software development practices and tools (e.g., JIRA, Confluence).
• Ability to collaborate effectively with cross-functional teams.

Preferred:

• Experience with Spark, PySpark, or similar distributed data processing frameworks.
• Databricks or cloud data engineering certification (or equivalent hands-on experience).
• Experience working with industrial IoT, telemetry, SCADA, WITSML, or other operational technology (OT) data sources.
• Background in Mechanical Engineering or related field is a plus.
• Familiarity with drilling, rig operations, condition monitoring, condition-based maintenance, and equipment reliability concepts is a plus.