Junior Data Engineer

They are seeking a Data Engineer / Analytics Engineer to help build and maintain the core experimental data platform that underpins scientific development, validation, and scale-up activities.

This is a hands-on, technically engaging role operating at the intersection of data engineering, analytics, and laboratory experimentation. You will be responsible for transforming raw, real-world experimental and sensor data into structured, trusted datasets used daily by scientists and engineers.

This position is ideally suited to someone who enjoys working with messy, real-world data and wants to contribute directly to the commercialisation of next-generation clean energy technology., * Build and maintain data pipelines for ingesting laboratory and plant data (CSV, Excel, sensor and time-series sources).

• Work closely with engineering and scientific teams to understand experimental data flows, formats, and validation needs.
• Clean, transform, and structure datasets for analysis, modelling, and reporting.
• Support the development of metadata standards to improve experiment traceability and comparability.
• Contribute to dashboards and analytical views used by R&D teams.
• Monitor data quality and investigate anomalies or pipeline issues.
• Improve documentation, data standards, and best practices.
• Progressively take ownership of operational data workflows under the mentorship of a senior data engineer.

You will ideally bring:

• Strong Python skills for data processing and analysis.
• Solid SQL capability and experience working with structured datasets.
• Experience or interest in time-series data and sensor-driven environments.
• A proactive, self-starting mindset with strong problem-solving ability.
• Comfort working within a fast-moving, technically complex start-up environment.
• A collaborative approach to working with scientists and engineers.

Desirable:

• Exposure to cloud platforms (GCP or AWS).
• Familiarity with analytics tools and dashboards.
• Experience with laboratory, scientific, or industrial datasets.
• Interest in hydrogen, energy systems, or electrochemistry.
• Understanding of ETL pipelines and data modelling concepts.

• Flexible start and finish times.
• Flexible hybrid and remote working.
• Support for international remote working.
• Pension: 3% employee / 5% employer.
• Team milestone celebrations.
• Referral bonuses.
• Strong exposure to a wide range of technologies and accelerated personal development.