Staff Backend Engineer - Data Platform- Seattle

Haus; Seattle (WA); On-site; USD 180,000 - 280,000; Full time

Benefits offered by this job

Flexible PTO

Equity

Health insurance

WFH stipend

Events & Offsites

Free Lunch

New Parent Leave

Job summary

Haus is hiring for a dual-depth role spanning backend systems engineering and data engineering. You will design services and pipelines that ingest data at scale and shape lakehouse/warehouse models to be trustworthy and reproducible.

The role leads the data platform powering the incremental platform, including ingestion from numerous APIs, warehouse integrations, and BigQuery workloads. You will mentor engineers and guide architectural decisions across GCP stack.

Qualifications

• 8+ years of software engineering experience with deep backend and data expertise.
• 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: design schemas that survive evolution and optimize complex analytical queries.
• Track record of Staff-level technical leadership: setting direction, writing design docs, guiding multiple workstreams.
• Excellent written and verbal communication; defend technical decisions to engineering, product, and exec stakeholders.

Responsibilities

• Architect and build the backend services powering Haus's data platform: high-throughput ingestion, normalization, data contracts, and orchestration.
• Solve hard distributed-systems problems in a data context: exactly-once semantics, idempotent reprocessing and backfills, schema evolution without downtime.
• 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 align with downstream teams.
• Mentor senior engineers and influence the broader org's data strategy.

Skills

Python

SQL/dbt

Distributed systems

Leadership

Communication

Backend engineering

Data quality

Tools

BigQuery

Snowflake

Databricks

Iceberg

Job description

About Haus

Haus is the causal marketing platform top businesses trust to optimize billions in ad spend worldwide. With support from PhD economists, data scientists, and growth experts, Haus' AI-driven technology translates complex marketing measurement into clear action and outcomes, enabling brands like Dyson, Wayfair, Sonos, Fanduel, SharkNinja, and Intuit to optimize spend, accelerate growth, and make smarter marketing decisions at scale.

The Role

This 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.

Haus is an equal opportunity employer

We make hiring decisions without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, age, disability, veteran status, or any other protected status.

We believe diverse perspectives make us stronger and are committed to an inclusive culture where everyone feels seen, heard, and empowered to contribute. Bring your authentic self — we would love to hear from you.