AI Platform Engineer leading multidisciplinary teams building AI - powered applications and intelligent workflows at Valtech. Shape the future of experience through Data, AI, and emerging solutions.
About the role
- Senior Data Engineer at Supabase managing data pipelines from source to analysis. Collaborating with growth, finance, and product teams to drive business insights.
Responsibilities
- Own data from source to delivery. Design ingestion from source systems into BigQuery with Airflow (Cloud Composer), Dataflow, and Python loaders; model it in dbt; and deliver the analysis in Hex. No handoffs, no "that's not my layer."
- Build for 10x. We're growing fast, and the data is growing with us. Every pipeline and model you ship should survive the volume multiplying in the next few months. Reliability, cost, and partition strategy are part of the design, not an afterthought.
- Explain what's driving the numbers. When a metric moves, you find out why. You can trace a number from a Hex dashboard back through the dbt models to the raw source and tell the business what actually pushed it up or down.
- Work AI-first, and own the output. You lean hard on modern AI tooling (coding agents, LLMs) to move faster across the whole stack, but you stay accountable for what lands in production. You know the difference between letting AI draft and letting AI decide, and you keep correctness, cost, and ownership in your own hands. This matters a lot to us.
- Partner directly with business teams. You don't wait for tickets. You understand what growth, finance, and product are trying to learn, get ahead of it, and translate messy questions into models and answers they can trust.
- Manage infrastructure as code. Provision and evolve the data platform with Pulumi, and treat the pipeline as a production system you're on the hook for.
- Stay on the frontier. You actively track what's new in data engineering and AI, and you bring the good tools in instead of waiting for someone to tell you about them.
Requirements
- Have 5+ years building and operating production data pipelines and warehouses
- Are deep with our stack or close equivalents: GCP, BigQuery, dbt, Airflow, Dataflow, Metaplane, Hex, and infrastructure as code (Pulumi or Terraform)
- Write strong SQL and can both build the pipeline and read the metric. You're an engineer who can do analysis, not one or the other
- Already build AI into how you work day to day, and have a clear sense of where a human has to stay in the loop
- Communicate clearly with non-technical stakeholders and chase down what they actually need
- Are comfortable navigating ambiguity, moving quickly, and designing for scale from the start
- Are genuinely passionate about data, with the track record to back it up
Benefits
- Fully Remote
- ESOP
- Tech Allowance
- Health Benefits
- Annual Off-Sites
- Flexible Work
- Professional Development
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