Software Engineer – Science Platform

Haus

Software Engineer focused on developing data pipelines and statistical systems for Haus's Science Platform. Collaborating with scientists and engineers to optimize marketing impact measurement.

Posted 7/10/2026full-timeSeattle • Washington • 🇺🇸 United StatesMid-LevelSenior💰 $165,000 - $205,000 per yearWebsite

Tech Stack

Tools & technologies

AirflowBigQueryCloudETLGoogle Cloud PlatformKubernetesNumpyPandasPythonSQL

About the role

Key responsibilities & impact

Build and evolve the data pipelines that fetch, aggregate, and transform KPI data from BigQuery across multiple geographies and granularities
Extend and maintain the statistical estimation library — implement new estimators, improve standard error methods, and optimize performance for large panel datasets
Improve the Metaflow-based analysis orchestration system that schedules and executes thousands of daily experiment analyses on Kubernetes
Design for reliability: build monitoring, alerting, and self-healing patterns for pipelines that run autonomously every day
Collaborate closely with applied scientists to translate research prototypes into production-grade code with proper testing, error handling, and observability
Work with product engineers to ensure analysis results are published correctly and flow cleanly into the customer-facing API and frontend
Use AI development tools as part of your daily workflow to accelerate delivery and explore solutions
Participate in on-call rotation and own the operational health of the science platform systems

Requirements

What you’ll need

3+ years of experience building and shipping production software systems
Must have strong Python proficiency — you write clean, well-tested Python and are comfortable with the ecosystem (pandas, numpy, pytest, poetry)
Experience with data-intensive applications: you've worked with large datasets, data pipelines, or ETL systems and understand the tradeoffs
Experience with SQL and analytical databases (BigQuery, Snowflake, or similar) — you can write performant queries and understand how warehouse-scale data processing works
Comfort with cloud-native environments (GCP preferred): you understand how to deploy, monitor, and operate services in production
Experience with workflow orchestration frameworks (Metaflow, Airflow, Dagster, Prefect, or similar) is a strong plus
Track record of working effectively with AI development tools (Claude, Cursor, Copilot, or similar) — you've integrated them into your workflow and can articulate how they change the way you build software
Ability to collaborate productively with scientists and researchers — you don't need a PhD, but you should be comfortable reading statistical code, understanding experimental design concepts, and asking good questions
Excellent communication skills — you can explain technical tradeoffs clearly and work effectively across disciplines

Benefits

Comp & perks

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

ATS Keywords

✓ Tailor your resume

Applicant Tracking System Keywords

Tip: use these terms in your resume and cover letter to boost ATS matches.

Hard Skills & Tools

Data Pipeline DevelopmentStatistical EstimationPython ProgrammingSQL QueryingETL SystemsCloud DeploymentPerformance OptimizationMonitoring and AlertingData AnalysisError Handling

Soft Skills

CollaborationCommunicationProblem-SolvingAdaptabilityCuriosity