- Own the design and implementation of the data platform, including its warehouse, replication, orchestration, transformation, and semantic layers.
- Build reliable pipelines that replicate production data into the warehouse while handling PII, multi-tenancy, and data residency constraints.
- Design and tune data systems for query performance, cost, recoverability, and observability.
- Build automated data quality checks, tests, and validation into pipelines and models.
- Define patterns for data grain, slowly changing dimensions, multi-tenant access controls, and row-level security.
- Build dbt models and Cube models and measures that provide governed metrics to BI tools, product reporting, and internal dashboards.
- Partner with Product and Engineering on data needs, event instrumentation, schemas, and production data pipelines.
- Support Customer Operations, GTM, and Finance with operational, sales, revenue, billing, and financial data.
- Improve platform reliability through monitoring, alerting, incident response, post-mortems, tooling, and documentation.
- Identify platform gaps and scaling bottlenecks, evaluate new capabilities, and align data infrastructure with broader AWS, Kubernetes, and security patterns.
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