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Data Engineer Python SQL AWS
Job summary
A growing tech startup in the UK seeks a Data Engineer to design and implement robust data pipelines for AI-based systems in fish farming. The role involves working on scalable data infrastructure and supporting AI/ML workflows. The ideal candidate will have experience in Python, SQL, and AWS, contributing to innovative solutions in a remote environment.
Qualifications
- Experience in designing and implementing data pipelines.
- Proficient in Python and SQL.
- Familiarity with AWS and machine learning technologies.
Responsibilities
- Design, build, and implement robust data pipelines.
- Work on scalable data infrastructure.
- Support high-volume data processing and AI/ML workflows.
Skills
Would you like to work on complex and interesting AI based systems with a team of tech entrepreneurs?
You could be joining a growing start-up that is utilising Machine Learning and AI technology to revolutionise fish farming, improving fish health and growth; their carbon neutral technology is already making a difference in Scotland, Chile, Canada, Australia, Spain and Norway and the company has ambitious growth plans.
- Design, build and implement robust data pipelines that transform raw IoT sensor data into actionable insights for fish farmers worldwide.
- Work on scalable data infrastructure, from ingesting real‑time sensor streams to building analytics‑ready datasets, enabling data‑driven decision making and improving operational efficiency across the global farm network.
- Support high‑volume data processing, data quality management and AI/ML workflows.
- Contribute to career progression opportunities and become an integral part of a small, distributed team.
Location / WFH : Remote UK.
* The salary benchmark is based on the target salaries of market leaders in their relevant sectors. It is intended to serve as a guide to help Premium Members assess open positions and to help in salary negotiations. The salary benchmark is not provided directly by the company, which could be significantly higher or lower.