- Build and maintain production data pipelines within established patterns and governance, ensuring reliability and performance at multi-terabyte scale.
- Exercise architectural judgment on data modeling, pipeline design, and platform usage, translating complex business requirements into scalable data solutions.
- Engage proactively with product and engineering stakeholders to translate requirements into data solutions, serving as the primary onshore technical point of contact.
- Drive platform quality through code reviews, testing practices, and engineering standards.
- Serve as onshore escalation point and institutional knowledge backup for platform decisions, reducing single-point-of-failure risk.
- Implement data pipelines that serve multiple product lines (Transfer Pricing, R&D Services, RoyaltyStat, Provisioning).
- Lead pipeline implementation for migrating multi-terabyte datasets from legacy systems to Databricks.
- Provide senior judgment, own problems end-to-end, make independent architectural decisions, and mentor engineers.
- Bridge the gap between product teams and data infrastructure, translating business requirements into data solutions.
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