About the role
Alpaca is hiring a Staff Analytics Engineer to own the future of its data warehouse. The Analytics Engineering team turns hundreds of millions of daily events from transactional databases, API logs, CRMs, payment systems and marketing platforms into the datasets behind partner invoicing, regulatory reporting, executive KPIs, partner-facing products and a growing number of AI agents. You will work across Data Platform, Data Scientists, business users and leadership.
The role sets multi-quarter technical direction for warehouse layering, domain boundaries, materialization and incremental strategies, keeping more than 1,000 dbt models fast, testable and cost-efficient. You will decide which models are served through ad hoc OLAP queries, which belong in a real-time analytics engine, and which become governed metrics in a semantic layer. You will also define data contracts, freshness SLAs, CDC or.
Highlights
- Set multi-quarter warehouse architecture direction across staging, intermediate and marts layers
- Choose serving paths across lakehouse OLAP, real-time engines and a semantic layer
- Guarantee cent-level accuracy on financial data with tests, reconciliation and write-audit-publish
- Mentor engineers and set org-wide modeling, testing and CI/CD standards
This recap is dataskew's editorial summary, not the company's copy.