Aios Medical is hiring a Data Engineer Lead to take full ownership of our data infrastructure. You will build reliable pipelines, make data accessible across all teams, and set the foundations for a future centralized data team. You'll start within the engineering team, focused on fixing broken pipelines and syncing 20+ sources into Redshift, while also defining critical business metrics across the customer journey.

What You'll Do

Own the flow of data from 20+ sources into Redshift, reducing manual checks, fixing failure points, and ensuring smooth operation.
Own the data tools, build the warehouse structure, and make decisions around sync frequency, tooling, and reliability.
Support both sides of the business: Growth (e.g., CAC, CPL, funnel metrics) and Product/Ops (e.g., time to medication, delivery times).
Build the backend logic to track key business metrics, defining what matters and how to measure it.
Over time, build a horizontal Data team that owns both data engineering and analytics across the organization.
Become a key decision-maker on data across the org, balancing reliability, speed, and clarity.

What We're Looking For

5+ years of experience working with data, with at least 2+ years focused on data engineering.
Experience owning pipelines, warehouses, and reporting in fast-moving environments.
Built and maintained data pipelines syncing from multiple sources into a central warehouse like Redshift.
Experience with Redshift or a similar cloud warehouse as the core of your stack.
Fluent in SQL; can build queries from scratch, troubleshoot broken ones, and define metrics clearly.
Understands business metrics and can break them down into required data points and build them end-to-end.
High ownership; figures out what matters, how to define it, and how to track it without being told.
Autonomy; can prioritize, unblock yourself, and move fast without waiting on others.
Team builder; has managed a team before and is excited to grow a team covering data engineering and analytics.

Nice to Have

Experience supporting teams measuring CAC, CPL, funnel stages, or other acquisition metrics.
Experience with operational metrics in healthcare or similar industries (e.g., fulfillment speed, delivery time).
Experience with analytics tools like Metabase or similar for data exploration and visualization.
Experience with customer data platforms like Rudderstack (or Segment).
A 'figure it out' mentality; digs deep to debug failing syncs, validate numbers, or reverse engineer broken reports.