Design, build, and maintain scalable data manufacturing pipelines using Databricks and PySpark; integrate new energy data sources; modernize ETL processes; and drive LLM/GenAI integration into extraction and transformation workflows while collaborating with engineering, QA, and product teams.

Design, develop, test, deploy, and maintain databases, services, and automated data pipelines. Write maintainable Python and database code, support production platforms, analyze requirements and data, and collaborate with product, design, and engineering teams in an Agile environment. The role also involves architecture, CI/CD, customer-focused solutions, and modern workflow orchestration tools.

Design, build, and maintain scalable data manufacturing pipelines (Databricks/PySpark) to ingest, standardize, and deliver energy and geoscience data. Integrate GenAI for extraction, consolidate overlapping datasets, mentor juniors, and define engineering standards while ensuring CI/CD, orchestration, and cloud best practices.