Data Engineer

Responsibilities

• Assist with developing a data ecosystem that is robust, fast, and scalable.
• Design, build and launch efficient & reliable data pipelines to move and transform data (both large and small amounts)
• Optimize existing pipelines and maintain of all domain-related data pipelines.
• Deploy inclusive data quality checks to ensure high quality of data.
• Use DevOps methodologies to create automated, efficient CI/CD processes to reduce the time to promote, test, and deploy Analytics models and analyses.
• Develop, test, deploy, and maintain efficient and reusable patterns of streaming and batch data ingestion pipeline architectures.
• Document and maintain architecture and coding standards for supported platforms.
• Participate in all phases of the software development lifecycle, including requirements gathering, technical planning, design, development, testing, sustaining support, and documentation.
• Seek guidance when a direction is needed and speak up about technology risks identified.
• Follow agile practices, as well as quality management procedures as defined by precedents, standards, or policies.
• Collaborate with the Analytics team members and teams across NOV to deliver solutions and evolve products.
• Comply with all NOV Company and HSE policies and procedures.

Minimum Qualifications

• Bachelor’s degree in computer science, Computer Engineering, relevant technical field, or equivalent practical experience.
• 3+ years of Python, PySpark or other modern programming language development experience.
• Hands-on experience working with data pipelines using a variety of source and target locations (e.g., Databricks, SQL Server, Data Lake, file-based, SQL and No-SQL database). 
• 3+ years of experience in custom ETL design, implementation, and maintenance.
• Experience developing batch ETL pipelines; real-time pipelines are a plus.