- Build and evolve the data platform foundations that make it easy and safe for others to ship dbt work (project structure, environments, permissions, patterns, documentation)
- Establish and maintain standards and guardrails for dbt development (testing strategy, source freshness, documentation, code review practices)
- Improve the developer experience for data workflows, including CI/CD, automated checks, and repeatable deployment patterns
- Manage data infrastructure as code with Terraform, including pipelines, IAM, and environments
- Improve and troubleshoot CDC replication from MySQL to BigQuery with Datastream
- Build tooling for backfills, drift detection, and reconciliation between source databases and the warehouse
- Contribute to infrastructure decisions on data ingestion and platform evolution, including latency, throughput, and alternative CDC approaches
- Partner with Analytics and Finance to define and deliver trusted metrics and dashboards in Looker
- Build and maintain analytics-ready datasets that support self-serve reporting and experimentation
- Support customer-facing, multi-tenant reporting with a focus on correctness, tenant isolation, and query performance
- Develop and optimize BigQuery data models for analytics and product use cases
- Implement ELT best practices in dbt, including testing, documentation, and versioning
- Design, build, and maintain scalable data pipelines using Python, dbt, and containerized jobs on GKE
- Ensure data quality, reliability, and observability for critical datasets and reporting
- Optimize performance and cost across BigQuery and data pipelines
- Integrate data workflows with backend services and APIs
- Work with Product and Engineering to translate business needs into data solutions
