Top Data & Analytics Jobs

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.

The Manager, Power Markets will conduct market analysis, develop forecasts, manage datasets, collaborate with teams, and communicate findings to stakeholders.

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.

Lead technical implementation of a market management platform for nodal electricity markets. Design and operate large-scale, data-intensive production systems handling continuously changing data. Make architecture decisions, contribute production software, manage incidents, improve existing systems, and partner with product, engineering, data science, and power-market experts. Lead technical reviews, mentor engineers, and drive optimization, forecasting, and analytical capabilities.

Design, implement, and maintain automated tests for ETL and data-driven products. Validate datasets against acceptance criteria, log and track defects, debug complex issues, and collaborate with cross-functional teams. Write clean test code and apply AI tools to accelerate test development.

The Principal Analyst, Large Load Intelligence at Enverus leads research on large loads and data centers, evaluates site attractiveness, and integrates insights into client strategies. Responsibilities include interpreting utility rate cases, publishing research, and engaging with stakeholders in the energy sector.

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.