Assembled is looking to solve the problem of scaling, maintaining, and trusting the metrics exposed by their legacy Go-based system. They need to build a new analytics stack that enables fast, reliable metric queries and simplifies the development of new reports, while also supporting customer-facing product experiences that require both large-scale analytical queries and low-latency, user-triggered interactions.
Requirements
- Have experience working with modern data warehouses (e.g., Snowflake, BigQuery) and understand their performance characteristics
- Have built or maintained end-to-end ELT pipelines and are comfortable choosing the right level of precomputation
- Have designed or worked closely with a metrics or semantic layer, and understand how to define metrics that are consistent, queryable, and performant across reporting surfaces
- Are comfortable reasoning about systems tradeoffs—latency, cost, developer velocity, and reliability
- Have strong SQL fluency and are comfortable reading query plans, debugging slow queries, and optimizing for performance
- Experience with semantic layer tools like Cube, MetricFlow, or Looker’s LookML
- Familiarity with analytics-focused software engineering (e.g., event tracking, funnel analysis, experiment platforms)
Responsibilities
- Design and build systems that power both the storage and retrieval of analytical data
- Own the transformation layer that models data for fast, consistent metric queries
- Define and maintain the metrics layer that supports dashboards, exports, APIs, and internal tools
- Collaborate with product, infrastructure, and Assist teams to build rich reporting experiences—like helping customers measure ROI on AI adoption
- Manage scalable pipelines that move and transform production data for analysis
- Instrument observability into the data platform, including freshness, lineage, and correctness
Other
- Take pride in building systems that are clear, maintainable, and empower others
- Experience modernizing legacy data systems or planning large-scale migrations
- Experience collaborating cross-functionally with AI/ML teams or product managers focused on AI systems
- Hybrid work model with catered lunches everyday (M-F), snacks, and beverages in our SF & NY offices
