Job Description

Summary

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GE Vernova is accelerating the path to more reliable, affordable, and sustainable energy, while helping our customers power economies and deliver GE Vernova is accelerating the path to more reliable, affordable, and sustainable energy, while helping our customers power economies and deliver the electricity that is vital to health, safety, security, and improved quality of life. Are you excited at the opportunity to electrify and decarbonize the world?



We are seeking a dynamic, forward-thinking, and results-driven Data Engineer to join our Grid Innovation team. This role focuses on designing, building, and maintaining the infrastructure and data pipelines that enable effective data collection, processing, storage, and analysis for cutting-edge AI/ML applications in the energy domain.



Experience in the energy sector, smart infrastructure, or industrial automation is fundamental, as this role supports AI-driven innovation in mission-critical systems with high regulatory and operational complexity.



As part of the CTO organization, reporting to the AI Leader, you will work closely with Grid Automation (GA) product lines, R&D teams, product management, and other GA functions. You will also support cross-functional initiatives by developing scalable and unified data frameworks to address critical customer problems and enable rapid prototyping and deployment, both at the edge and in the cloud.

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Essential Responsibilities:

Design and maintain database architectures, schemas, and data models tailored to grid innovation and energy system applications. Utilize efficient data storage technologies (e.g., Relational Databases, Data Lakes, NoSQL) to ensure scalable and secure data access. Build, optimize, and maintain reliable data pipelines for data ingestion, cleaning, transformation, and feature extraction from structured and unstructured sources. Develop and manage integrations with internal and external data sources and APIs to enable seamless data flow. Identify new and relevant datasets to improve product capabilities and decision-making across the business. Automate data integration and transformation workflows for diverse data formats and operational needs. Monitor performance and scalability of data systems, and implement enhancements to increase efficiency and reliability. Apply data governance policies and implement data quality checks to ensure data integrity across systems. Collaborate with Data Scientists, ML Engineers, and other technical stakeholders to deliver relevant, ready-to-use datasets. Work closely with product management and R&D teams to gather requirements and develop innovative data solutions that support product development.

Must-Have Requirements:

PhD, Master's, or Bachelor's degree in Computer Science, Electrical/Computer Engineering, or a related field with a focus on data engineering or electric power engineering. Proven experience in the energy sector, smart infrastructure, or industrial automation, such as electric power systems, smart grids, connected buildings, utilities, SCADA/PLC systems, or Industry 4.0 platforms Significant experience in data engineering, with hands-on expertise in building and managing data pipelines. Proficiency in Python, SQL, and at least one other programming language commonly used in data engineering (e.g., Scala, Java). Experience with relational databases (e.g., PostgreSQL) and NoSQL databases (e.g., MongoDB, Cassandra). Familiarity with cloud platforms like AWS, Azure, or GCP for deploying and managing data systems. Extensive experience with ETL processes (Extract, Transform, Load) and automating data pipeline workflows. Effective communication skills, with the ability to collaborate smoothly with cross-functional teams and resolve conflicts proactively.Adaptability to work in a dynamic, multi-tasking environment, with the ability to address evolving challenges.

Nice-to-Have Requirements:

Several years of experience in data engineering or a related field, with expertise in designing scalable data solutions. Familiarity with big data technologies like Hadoop, Kafka, or Spark for processing large-scale data. Experience with data visualization tools such as Tableau, Power BI, or similar platforms for building reports and dashboards. Hands-on experience with GraphDB, SQL/NoSQL databases, and data warehousing technologies like Snowflake or Redshift.

At GE Vernova - Grid Automation, you will have the opportunity to work on cutting-edge projects that shape the future of energy. We offer a collaborative environment where your expertise will be valued, and your contributions will make a tangible impact. Join us and be part of a team that is driving innovation and excellence in control systems.

About

GEV

Grid Solutions:

At GEV Grid Solutions we are electrifying the world with advanced grid technologies. As leaders in the energy space our goal is to accelerate the transition for a more energy efficient grid to full fill the needs of tomorrow. With a focus on growth and sustainability GE Grid Solutions plays a pivotable role in integrating Renewables onto the grid to drive to carbon neutral. In Grid Solutions we help enable the transition for a greener more reliable Grid. GE Grid Solutions has the most advanced and comprehensive product and solutions portfolio within the energy sector.

Why we come to work:

At GEV, our engineers are always up for the challenge - and we're always driven to find the best solution. Our projects are unique and interesting, and you'll need to bring a solution-focused, positive approach to each one to do your best. Surrounded by committed, loyal colleagues, if you can dare to bring your ingenuity and desire to make an impact, you'll be exposed to game-changing, diverse projects that truly allow you to play your part in the energy transition.

What we offer:

A key role in a dynamic, international working environment with a large degree of flexibility of work agreements


Competitive benefits, and great development opportunities - including private health insurance.

Additional Information

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Relocation Assistance Provided:

No