Work with project teams and clients to build data systems to drive social impact.

Responsibilities

• Working with clients to understand their current processes and pain points, and identifying which of these can be addressed through automating and streamlining data flows.
• Designing, building, and maintaining optimal data pipeline architecture.
• Designing, building, and maintaining data warehouses and data lakes.
• Synthesising, visualizing, and communicating results: dashboards, plots, interactive viz, presentations, and reports to provide actionable data insights to decision-makers.
• Making thoughtful decisions about application architecture, data flows, integrations, and user-facing behavior to support scalable, production-grade solutions.
• Working closely with clients, other engineers, product owners, and domain experts to review code, plan releases, and deliver features end-to-end.
• Writing blog posts or presenting on lessons learned.
• Supporting teammates through formal and informal coaching and collaboration that enables continuous learning and improvement for the team.

Skillset

• Experience of at least 1+ year in data engineering, with proficiency in Python and SQL for building production systems.
• Proficiency building ELT pipelines in a production setting.
• Proficiency with data modelling techniques.
• Proficiency working with OLTP and OLAP data stores.
• Proficiency in Flask/FastAPI or similar backend frameworks.
• Experience working with a cloud hosting platform like AWS or GCP.
• Sound foundations in statistics and probability.
• Ability to independently scope, design, and deliver end-to-end features.
• Clear written and verbal communication skills for collaborating with technical and non-technical stakeholders.
• A willingness to pick up new skills and technologies (e.g., front-end) based on project and team needs.

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