Staff Backend Engineer - Data Platform

Responsibilities

• Architect and build backend services for high-throughput data ingestion, normalization, data contracts, and orchestration.
• Solve distributed-systems problems involving exactly-once semantics, idempotent reprocessing and backfills, schema evolution, and unreliable third-party APIs.
• Own lakehouse and warehouse schema design, data models, dbt architecture, data quality, lineage, and BigQuery cost and performance.
• Set engineering standards for testing, API design, code review, observability, and delivery practices.
• Drive architectural decisions across the GCP, BigQuery, dbt, and Python stack.
• Set technical direction, mentor senior engineers, and influence broader data strategy.

Requirements

• 10+ years of software engineering experience with deep backend and data expertise.
• Hands-on experience with a cloud data warehouse or lakehouse; BigQuery is preferred, with Snowflake, Databricks, or Iceberg-based stacks also considered.
• Deep SQL and dbt experience, including designing schemas for evolution and reasoning about analytical query correctness and performance.
• Expert-level Python experience building production services rather than only scripts or notebooks.
• Track record of Staff-level technical leadership across multiple workstreams, including setting direction and writing design documents.
• Strong written and verbal communication skills for defending technical decisions to engineering, product, and executive stakeholders.
• Experience spanning both production backend services and data pipelines is required; strength in only one area is insufficient.
• Contributions to Apache Spark, Beam, Iceberg, Arrow, or similar open-source data frameworks are a bonus.

Benefits

• Flexible PTO.
• Equity participation in the startup's success.
• Health, dental, and vision insurance with multiple plan options.
• WFH stipend.
• Events and offsites.
• Free lunch when working from the office in San Francisco, New York City, or Seattle.
• New parent leave.
• Preference for candidates within commuting distance of offices in San Francisco, Seattle, or New York City; the company values in-person collaboration.