Associate Scientific Software Engineer
Role details
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Tech stack
Job description
As an Associate Scientific Software Engineer, you'll help build the data foundations that power OQC's quantum hardware development. Working alongside scientists and engineers, you'll develop data pipelines, improve data quality and create tools that transform complex experimental data into insights that accelerate innovation., This is an exciting opportunity for a STEM graduate who enjoys software development, data engineering and solving real-world technical challenges. You'll work with experimental and manufacturing data, helping to improve how information is captured, organised and analysed while developing your skills in scientific software engineering within a world-leading quantum computing company. What You'll Be Working On
- Develop and maintain data ingestion pipelines for experimental and manufacturing data.
- Investigate and resolve data quality, validation and ingestion issues to ensure reliable datasets.
- Build and improve database schemas, data models and analytics tools that support engineering teams.
- Create dashboards and visualisations that provide valuable insights into fabrication and measurement processes.
- Collaborate with scientists, engineers and nanofabrication teams to improve data accessibility and decision-making.
- Document systems, data flows and engineering processes to support scalable software development.
- Contribute to scientific software, automation tools and measurement systems that enable quantum hardware development.
Requirements
- A degree in Physics, Mathematics, Engineering, Computer Science or another STEM discipline.
- Strong Python programming skills.
- Experience using data analysis tools such as Pandas, NumPy and Jupyter.
- Excellent attention to detail with a focus on data quality and organisation.
- Strong analytical and problem-solving skills, with the ability to investigate complex datasets.
- Confidence working with messy, real-world experimental or engineering data.
- A collaborative mindset and enthusiasm for learning while working closely with scientists and engineers.
The 'Nice-to-Haves'
- Experience with Git, testing and software development best practices.
- Experience with SQL, PostgreSQL, MongoDB or other database technologies.
- Experience building dashboards or data visualisation tools.
- Experience working with scientific, manufacturing or measurement data.
- Knowledge of ETL/ELT pipelines, Linux or cloud infrastructure.
- Exposure to automation or scientific software development.