Consulting Data Engineer

Responsibilities

• Leading the development of the Supply Trace ‘data warehouse’ ETL pipelines.
• Cleaning, indexing, and cross-referencing bill-of-lading and risk evidence data.
• Designing and deploying the ETL pipelines at scale in the cloud.
• Contributing to team ways-of-working and culture development.
• Close collaboration with Supply Trace Technical Lead, Product Manager and UX Advisor, as well as Supply Trace leadership (a CTO is also currently being recruited).
• Provide strong peer leadership and guidance to the other technology team members, fostering a culture of collaboration and continuous learning, and influencing agile software development practices and culture-building.

Skillset

• Expert Python (Pandas/Polars, Dask) and SQL programming skills (Essential).
• Expert cloud-native data engineering experience, preferably with Google Cloud Platform (BigQuery, DataProc, Cloud Build, Cloud Run) (Essential).
• Expert CloudOps and DevOps skills and experience (CI/CD, Github Actions, containerisation, orchestration) (Essential).
• Expert technical operations experience (Agile frameworks) (Essential).
• Experience in working with distributed and / or fully remote teams (Essential).
• Experience in, or a desire to be a part of, a start-up and / or small team environment (Essential).
• Masters degree (or above) in a relevant technical field (Computer Science, Software Engineering, Machine Learning, or some other STEM field) (Desirable).
• Experience in Tech for Good (Desirable).
• Experience working with academic institutions (Desirable).
• Experience in global supply chain software, open data and/or open-source projects (Desirable).
• Domain knowledge in shipping and supply chains (Desirable).
• Domain knowledge in corporate and risk data, especially labor and climate risk (Desirable).
• Experience in data product management, and/or data quality analysis (Desirable).
• Machine learning technical skills and experience (Desirable).