The RoleThis is a dual-depth role:
backend systems engineering + data engineering. You'll design the services and pipelines that ingest data at scale and the lakehouse/warehouse models that make it trustworthy and reproducible.
Haus's Data Platform powers the entire incrementality platform: every causal experiment, every marketing mix model, every dollar of ad spend we help customers reallocate runs on systems this team builds. Under the hood, that platform is a set of distributed backend services - ingestion from dozens of ad-network APIs, customer warehouses, and partner tools; normalization and validation layers; orchestration and observability infrastructure - feeding BigQuery whose models must be correct, because our customers make million-dollar decisions on the outputs.
You will lead the team, setting technical direction, contributing hands-on and partnering with engineering and product leaders.
What you'll do- 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.
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.
You might be a great fit if- You're passionate about data - pipelines, lakehouses, warehouses, the craft of making data trustworthy at scale.
- You're equally strong at backend engineering: production services, APIs, distributed systems.
- You're the engineer who reviews both the service PR and the dbt PR, and holds them to the same standard.
This role is probably not for you if- Your experience is primarily SQL/dbt transformations, BI, or analytics engineering without significant backend service development.
- You've operated data tools (Airflow, Fivetran, dbt) as a user, but haven't designed and written the production systems underneath them.
- You're a strong backend engineer who sees warehouse and data-model work as someone else's job.
Bonus points- Contributions to open-source data frameworks or tooling (Apache Spark, Beam, Iceberg, Arrow, or similar).
Interview process (what we test for)We interview for both halves of this role, strong backend + data experience. Candidates who are strong in only one half typically don't advance
What We Offer We're a high-performance, low-ego team operating in a fast-moving environment. We care deeply about our customers and expect everyone to take full ownership of their work - this is a place where high expectations fuel even higher growth.
If you thrive in ambiguity, take pride in raising the bar, and want to work alongside top-tier peers who challenge and support you, you'll find unmatched opportunities here. If you're looking for predictability or rigid structure or you prefer order-taking to go-getting, we're probably not the right fit - and that's okay.
We work in small, mission-driven teams that prioritize inclusion, collaboration, and growth over hierarchy or red tape.
Some of our benefits include:
- Flexible PTO - take time when you need it!
- Equity - Startup environment with part-ownership in our successes
- Top of the line health, dental, and vision insurance - multiple plan options so you can pick what fits you best
- WFH stipend to support the set up you need to be productive
- Events & Offsites - opportunities to connect and celebrate in real life!
- Free Lunch - Grab a bite on us when you choose to work from the office (hub locations include SF, NYC and Seattle)
- New Parent Leave - take time to welcome your newest Hausmate
We value in-person collaboration at Haus and give preference to candidates within commuting distance of our offices in San Francisco, Seattle, and New York City.
