Staff Backend & Data Platform Architect

Haus; San Francisco (CA); On-site; USD 180,000 - 260,000; Full time

Benefits offered by this job

Flexible PTO

Equity

Health, dental, and vision insurance

WFH stipend

Events & Offsites

Free Lunch (SF, NYC, Seattle)

Job summary

Haus is seeking a leader who will design and scale its data platform. You will guide backend services and data pipelines that ingest data from dozens of sources and feed a scalable lakehouse on BigQuery.

Expect hands-on work, architectural direction, and cross-functional collaboration with product and data science teams. You will mentor senior engineers, set technical direction, and drive a cohesive data strategy across the stack.

Qualifications

• 8+ years of software engineering experience, with deep backend and data expertise.
• Solid, hands-on experience with a cloud data warehouse or lakehouse (BigQuery preferred; Snowflake, Databricks, or Iceberg-based stacks).
• Expert-level Python experience for building services, not just scripts or notebooks.
• Deep SQL/dbt experience: you can design schemas that survive evolution, reason about correctness and performance of complex analytical queries.
• Track record of Staff-level technical leadership: setting direction across multiple workstreams, writing design docs others build from, and being the engineer the team pulls in on the hardest problems.
• Excellent written and verbal communication; able to defend technical decisions to engineering, product, and exec stakeholders.

Responsibilities

• Architect and build the backend services that power Haus's data platform: high-throughput ingestion from third-party APIs, normalization services, data contracts, and the control plane that orchestrates it all.
• Solve hard distributed-systems problems in a data context: exactly-once semantics, idempotent reprocessing and backfills, schema evolution without downtime, graceful handling of flaky third-party APIs at scale.
• Own the lakehouse/warehouse as a product: schema and data-model design, dbt architecture, data quality frameworks, lineage, and cost/performance of BigQuery workloads.
• Set the engineering bar for the team — testing strategy, API design, code review, observability, CI/CD.
• Drive architectural decisions across our GCP / BigQuery / dbt / Python stack and drive alignment with downstream engineering and data science teams.
• Mentor senior engineers and influence the broader org's data strategy.

Skills

Backend engineering

Data engineering

Python

SQL/dbt

Distributed systems

Leadership

Communication

Tools

BigQuery

Snowflake

Databricks

Iceberg

dbt

Airflow

Job description

Haus is seeking a leader who will design and scale its data platform. You will guide backend services and data pipelines that ingest data from dozens of sources and feed a scalable lakehouse on BigQuery.

Expect hands-on work, architectural direction, and cross-functional collaboration with product and data science teams. You will mentor senior engineers, set technical direction, and drive a cohesive data strategy across the stack.