Data Engineer

IMC is launching a new power and gas trading business in Århus, Denmark, the hub for power and gas trading in Europe. We are dedicated to creating a strong, independent, Århus-based team with local leadership while drawing on IMC's more than 30 years of global trading expertise. We are looking for experienced professionals in power and gas trading and technology to join the team.

Your Core Responsibilities

As a Data Engineer in our energy trading team, you will build and operate the data backbone that enables real‑time trading and advanced analytics. You will play a key role in ensuring that our traders, quants, and researchers have access to high‑quality, reliable, and scalable data. Your responsibilities will include:

• Designing, building, and managing real‑time and historical data pipelines for energy trading use cases
• Ensuring data quality, availability, and reliability across trading platforms, exchanges, weather, and renewable production sources
• Designing and maintaining scalable, distributed data infrastructure
• Supporting both trade enablement and advanced research/analytics for algorithmic trading
• Contributing to strong software engineering practices, including automated testing, CI/CD, and dev/prod environment management
• Working closely with traders, quants, and developers to define evolving data needs and enable new use cases

This is a greenfield role: you will join a small team of developers led by an experienced tech lead. Over the next 12 months, the focus will be on scalable ingestion, trade data persistence, and research support.

Your Skills and Experience

• Solid Python skills, engineering non‑trivial applications (beyond ad‑hoc scripting)
• Knowledge of software engineering best practices (e.g. automated testing, CI/CD, dev/prod environments)
• Experience with non‑trivial data use cases; streaming data experience is a strong plus
• Exposure to infrastructure, ideally deploying or maintaining applications on Kubernetes
• Familiarity with distributed compute frameworks (Spark, Dask, etc.), with understanding of scaling challenges
• Background in energy, finance, or commodities is preferred
• Experience with Kafka, Docker, and big data technologies
• Strong understanding of ETL, real‑time data flows, and data architecture
• Open about what you don’t know and eager to learn quickly
• Not afraid of “dirty work” and proactive in automating repetitive tasks
• Collaborative, patient, and skilled at explaining technical concepts to non‑technical colleagues
• Strong problem‑solving and communication skills

About Us

IMC is a global trading firm powered by a cutting‑edge research environment and a world‑class technology backbone. Since 1989, we’ve been a stabilizing force in financial markets, providing essential liquidity upon which market participants depend. Across our offices in the US, Europe, Asia Pacific, and India, our talented quant researchers, engineers, traders, and business operations professionals are united by our uniquely collaborative, high‑performance culture, and our commitment to giving back. From entering dynamic new markets to embracing disruptive technologies, and from developing an innovative research environment to diversifying our trading strategies, we dare to continuously innovate and collaborate to succeed.

At IMC, we understand the importance of diversity, equity and inclusion, and are committed to continually improving this in our recruitment process. As part of our commitment, we have added an additional question below, to better understand our candidates, and focus our marketing, sourcing and interviewing efforts, to ensure equitable outcomes. This question is voluntary, and the information you provide will only be used for the purpose stated above and will not be shared with interviewers in the application process. If you do not wish to provide a response to the question, there will be no adverse impact on your application.

What is your gender/gender identity? Select...

By checking this box, I consent to IMC collecting, storing, and processing my responses to the demographic data surveys above.

#J-18808-Ljbffr