Senior Data Engineer (Multiple Locations)

DNV Germany Holding GmbH; United Kingdom; Hybrid; GBP 50,000 - 90,000; Full time

Job description

About Energy Systems

We help customers navigate the complex transition to a decarbonized and more sustainable energy future. We do this by assuring that energy systems work safely and effectively, using solutions that are increasingly digital. We also help industries and governments to navigate the many complex, interrelated transitions taking place globally and regionally, in the energy industry.

EVOLVE Intelligence accelerates the transition toward a carbon-free future through software and analytics. We are looking for a Senior Data Engineer to help us accomplish this mission.

Working with the Analytics & Data Science team in DNV – Energy Management’s Technology group is more than just a job; it’s an opportunity to be part of a collaborative community where you can learn, grow, and thrive. Join a dynamic and diverse technology team that values innovation, impact, and sustainability. Help us build scalable data solutions that support demand side management, demand flexibility, and transportation electrification programs!

As a Senior Data Engineer, you will play a key role in designing, building, and optimizing scalable data pipelines and foundational data infrastructure that power advanced analytics, machine learning models, and software solutions. You will work closely with software developers, analytics engineers, ML engineers, and data engineers to transform raw data into meaningful insights that help utility programs reduce emissions and support the clean energy transition.

Your contributions will enable high-quality, performant, and reliable data that serves as the backbone for decarbonization initiatives across energy efficiency, demand response, electrification, and distributed energy resources.

This role is based at any of our DNV offices in the US, presenting a dynamic hybrid schedule where employees will typically spend three (3) days per week working from a DNV office. Further details regarding role-specific requirements will be shared during the interview process.

What You'll Do

• Develop & Optimize Data Pipelines: Design and build ETL/ELT pipelines using Databricks, SQL, and Python to support data processing, analytics, and machine learning workflows.
• Architect & Automate Data Workflows: Implement data orchestration tools (e.g., Azure, Databricks Workflows) for scalable and automated data operations.
• Enable ML & Advanced Analytics: Support ML engineers and data scientists in feature engineering, data transformations, and operationalizing ML models.
• Ensure Data Quality & Reliability: Implement data validation, monitoring, and observability frameworks to ensure high data accuracy and availability.
• Optimize for Performance & Scalability: Apply distributed computing best practices to improve database and query performance.
• Leverage Cloud Technologies: Utilize Azure-based infrastructure for developing and deploying scalable cloud-native data solutions.
• Foster Collaboration & Best Practices: Work closely with software developers, ML engineers, and analytics engineers to align data engineering efforts with business goals.
• Contribute to DevOps & CI/CD: Implement testing, version control, and deployment automation for data pipelines using Azure DevOps.
• Mentor & Share Knowledge: Support team members and contribute to a culture of continuous learning and technical excellence.

What is Required:

• Bachelor’s degree in Computer Science, related discipline, or equivalent combination of education and work experience related to data engineering.
• Minimum of 5 years’ experience as a Data Engineer.
• Ability to manage work across multiple projects and handle context switching efficiently.
• Fluent in the following technologies and tools:
  • SQL (T-SQL, PostgreSQL)
  • Python
  • Databricks
• Strong written and verbal English communication skills.
• We conduct pre-employment drug and background screening.

What is Preferred:

• Experience in the Energy Industry would be a plus.
• Experience with Microsoft Azure, including Azure Containers, DevOps, and CI/CD setup within Azure DevOps and Azure ML Ops.
• Familiarity with event-driven architectures and real-time data processing.
• Experience working on and supporting the construction of ML models.
• Knowledge of distributed computing frameworks like Apache Spark.

*Immigration-related employment benefits, for example visa sponsorship, are not available for this position.*