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Tech Stack
Tools & technologiesAirflowAmazon RedshiftAWSBigQueryCloudPythonSQLTerraform
About the role
Key responsibilities & impact- Design, build, and maintain data pipelines that ingest from a variety of sources – third-party APIs, operational databases, and file-based exports – primarily in Python on AWS.
- Own and evolve our data warehouse architecture and shape where it goes next – assessing and moving toward a cleaner, centralised warehouse or lakehouse that's well-structured, reliable, and managed as code.
- Build a fast, safe path from "new data needed" to "available to analysts and the business." Our current release flow is reliable but slow; you'll streamline testing, releases, and the overall experience of adding and changing models.
- Implement transformation tooling so analytics logic is version-controlled, tested, and reviewable. We use dbt and intend to keep building around it.
- Make it easy and safe for engineers, analysts, and product teams to access the data they need, with appropriate controls and auditability in place.
- Establish monitoring, alerting, and data quality checks across critical pipelines.
- Partner with analytics, engineering, and product teams to make their work faster, safer, and more reliable – including code review, mentorship on engineering practices, and improving developer experience.
- Contribute to our data security and compliance posture in line with healthcare regulatory standards (ISO 27001, GDPR).
- Help define our longer-term data platform strategy as the team grows.
Requirements
What you’ll need- Solid experience as a data engineer or backend engineer working on production data systems.
- Strong SQL and strong Python for data work, including with large or distributed datasets.
- Experience designing and operating data pipelines in production – ingestion, transformation, orchestration.
- Experience with cloud data platforms, ideally AWS. Hands-on experience choosing and standing up a warehouse or lakehouse (e.g., Redshift, Snowflake, Databricks, BigQuery, or comparable) is highly valued.
- Familiarity with modern transformation and orchestration tooling – dbt, plus orchestration such as Airflow, Dagster, Step Functions, or equivalent.
- Infrastructure-as-code experience (e.g., Terraform/CloudFormation/CDK) and a habit of managing data infrastructure the same way.
- You've worked somewhere that grew quickly and felt first-hand how data systems built for an earlier stage start to creak – and you know how to rebuild them without bringing the business to a halt.
- Comfort working in a small team where you'll make architectural decisions, not just execute them.
- Clear communication – you'll work with engineers, analysts, and clinical/operational stakeholders.
Benefits
Comp & perks- Competitive compensation
- Opportunity to make a meaningful impact on healthcare outcomes
- Collaborative, inclusive culture focused on learning and innovation
- Ongoing professional development in emerging data technologies
- Flexible working with a commitment to work-life balance
ATS Keywords
✓ Tailor your resumeApplicant Tracking System Keywords
Tip: use these terms in your resume and cover letter to boost ATS matches.
Hard Skills & Tools
PythonSQLdata pipelinesdata transformationdata orchestrationinfrastructure-as-codedbtAWSdata warehousingdata quality checks
Soft Skills
clear communicationmentorshipcollaborationproblem-solvingdecision-makingadaptabilityteamworkleadershiporganizational skillsanalytical thinking
Certifications
ISO 27001GDPR