Big Data Engineer

About the role

National Oilwell Varco is seeking a passionate Big Data Engineer to help customers improve business impact through data and analytics. You will join a creative, highly‑motivated team driving innovation in the upstream oil field services industry.

Key responsibilities

• Design, develop, and optimise scalable data ingestion, transformation and analytics pipelines for IoT, operational and business data using Spark and Delta Lake.
• Create and tune Spark workloads—including batch, streaming and machine‑learning jobs—and optimise Spark clusters.
• Build reusable frameworks for ingesting, validating, enriching and processing large‑scale event‑driven datasets.
• Develop analytical data models, curated datasets and KPI calculation frameworks for product analytics, operational reporting and self‑service BI.
• Collaborate with product, engineering, operations and business stakeholders to define and maintain meaningful KPIs and data products.
• Implement real‑time and batch processing solutions using event‑based and streaming technologies.
• Execute large‑scale data migration from sources such as OSI PI and TimescaleDB to enterprise platforms.
• Develop monitoring, observability, reconciliation and automation tools for pipeline reliability, quality and performance.
• Support platform capabilities including APIs, data services and integrations within Agile and DevOps environments.
• Document architecture, data lineage, business logic, KPI definitions and operational procedures.

Required profile

• Bachelor’s degree in Computer Science, Information Systems or a related field (or equivalent experience).
• Minimum of 5 years of relevant experience in big‑data engineering.

Required skills

• Advanced knowledge of Apache Spark and/or Databricks, including cluster tuning.
• Experience with Delta Lake, distributed systems and data partitioning.
• Proficiency in .NET, C#, Python, JavaScript and Go.
• Strong background with AWS Cloud services and APIs.
• Hands‑on experience with OSI PI, TimescaleDB, PostgreSQL and SQL.
• Linux and Windows operating systems, containerisation technologies.