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Shape the future of energy trading — design and build scalable data platforms that power real-time trading decisions and accelerate the transition to sustainable energy.
Work at the intersection of data, cloud, and trading — collaborate with engineers, quants, and traders to deliver end-to-end, high-performance data solutions on Azure, Databricks, and Snowflake.
Innovate in a high-impact environment — join a cross-functional team where technical excellence, experimentation, and collaboration drive smarter, data-driven energy markets.
At Eneco, we’re working hard to achieve our mission: sustainable energy for everyone. Learn more about how we’re putting this into action in our One Planet Plan.
As a Data Engineer in energy trading you will help shape technical decisions for our data platform, from setting up cloud infrastructure to developing data pipelines and models. You will work closely with other engineers, quants, and stakeholders to design and deliver end-to-end solutions that ensure reliable, scalable, and innovative data systems supporting trading activities.
Must have:
Demonstrated expertise in designing, optimizing, and implementing large-scale data pipelines and ETL workflows, enforcing data quality, data governance and data modelling standards.
Software development best practices, including API design and development, code reviews, version control, automated testing, and CI/CD pipelines, with an interest in DevOps and SRE principles for reliable production deployments.
Our stack includes Python for data processing on Databricks, Snowflake, Kubernetes, DBT, Grafana for visualizations, and we primarily run on Azure. Proficiency in most of these tools is required, including advanced features.
Nice to Have:
Experience designing and maintaining ML model deployment pipelines, leveraging MLOps practices in Databricks to automate model versioning, testing, deployment, and monitoring at scale.
Familiar with key DS and ML processes and techniques, such as data cleaning and preprocessing, feature engineering, feature selection, model training and tuning, model evaluation, cross-validation, hyperparameter optimization, model deployment, and monitoring model performance in production environments.
Skilled in energy trading, building and optimizing data pipelines for algorithmic trading, integrating diverse market data, using standard connectivity and backtesting methods, and partnering with traders and quants to deliver robust, scalable solutions
You will be working alongside Data Engineers, Machine Learning Engineers, Data Scientists, Data Analysts, as well as quants and traders. Together, your team will drive innovation in energy trading, supporting the transition to more sustainable energy sources while ensuring energy security and making the solutions economically viable. Collaboration and continuous learning are at the heart of our team. We celebrate successes, learn from failures, and work together to deliver solutions that make a real impact.
Then please reach out to our Recruiter: [email protected]