- Manage, coach, and develop the data engineer on the team, with regular one-to-ones and clear goals.
- Set standards for data code review, testing, documentation, and on-call.
- Plan the team's work with Engineering, Finance, and Product, and coordinate as priorities shift.
- Own the Databricks lakehouse, including ingestion, modelling, data quality, and cost.
- Build and run pipelines from the production platform, Salesforce, NetSuite, and third-party sources.
- Maintain accurate, fast, self-serve internal reporting in Sigma, and make pipelines observable and recoverable.
- Run data processes for month-end close, revenue calculations, and vendor cost reconciliation; support audits and year-end reconciliation.
- Build and improve customer-facing data products, including the data connector and embedded reporting.
- Build data foundations for AI tools and agents, and identify opportunities to apply data and AI to the product and team workflows.
- Apply data management and privacy policies, and partner with InfoSec and Compliance on access, retention, and audit requirements.
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