- Deliver Flex-critical data needs: build and maintain reliable pipelines and datasets that enable Flex models.
- Evolve the data platform: assess current architecture and drive pragmatic improvements.
- Own data quality and trust: implement testing, lineage, and guardrails.
- Enable self-serve analytics: produce well-modeled datasets and documentation.
- Partner on data science work: collaborate on data readiness for modeling, feature pipelines, and evaluation workflows.
- Make high-leverage tech choices: propose and justify changes to tools and processes.