As a Data Engineer at Domin, you will join an ambitious team working across engineering, production, and data systems. You will work with data from across the business, including product test results, manufacturing process data, and production metrics, and turn it into something engineers and production teams can actually use. That means validating test results, running correlation analysis across different test methods and products, and structuring data so it flows reliably to the people who need it. The problems are technical and grounded, and you will be contributing useful work from the start.
Day to day, you will be writing Python, working with SQL, running analysis, and building or improving the pipelines and schemas that underpin how we store and access technical data. You will work closely with engineers across the business, understanding what they need from the data and helping deliver it in a form they can use. The work is hands-on and varied, with analytical tasks sitting alongside infrastructure work, and both matter.
Over time, you will take on more of the data infrastructure itself, improving pipelines, tightening database schemas, and helping define the standards that keep our data consistent as the business grows. Domin already deploys machine learning against real manufacturing data, and part of the longer-term opportunity in this role is contributing to the foundations that allow those capabilities to expand.
Key Responsibilities:
- Conduct data analysis and validation work on engineering and production projects, including correlation analysis and exploratory analysis of manufacturing and test data, presenting findings directly to engineering teams.
- Contribute to database schemas and data transformation pipelines, with code reviewed and merged to production standard
- Write and maintain Python scripts and pipelines that remove manual steps from data workflows, improving speed and repeatability
- Participate in code review and maintain documentation standards across scripts, queries, and pipelines
- Build familiarity with Domin’s machine learning and data-driven manufacturing workflows, contributing to the data foundations that allow those capabilities to grow
Essential Requirements:
- University degree in Computer Science, Software Engineering, Data Engineering, Data Science, or a related technical field.
- Strong proficiency in Python, including writing clear, well-documented, and reliable code.
- Good working knowledge of SQL and relational databases.
- Experience working with structured datasets and carrying out practical data analysis and transformation tasks, including the use of libraries such as Pandas and NumPy.
- Experience with version control using Git.
Beneficial Requirements:
- Strong problem-solving skills, attention to detail, and the ability to learn quickly in a hands-on engineering environment.
- Experience with cloud platforms such as Azure, AWS, or GCP, with Azure preferred.
- Understanding of Docker and containerisation.
- Familiarity with machine learning concepts and the data preparation work that supports them.
- Experience contributing to database design or schema development.
- Familiarity with engineering, manufacturing, or test data environments.
