Job Overview
Location
Seattle, WA
Job Type
Full-time
Category
Data Science
Date Posted
June 26, 2026
Full Job Description
đź“‹ Description
- • Lead the architecture and technical direction of Haus’s data ingestion and normalization platform, responsible for processing terabytes of daily data from ad networks (Google, Meta, TikTok, Amazon), Fivetran connectors, and customer data warehouses (Snowflake, BigQuery).
- • Design and implement high-leverage data systems including schema evolution, data contracts, data quality frameworks, idempotent backfills, lineage tracking, time-travel capabilities, and pipeline observability to ensure reproducibility and trust in downstream analytics.
- • Drive architectural decisions within the GCP / BigQuery / dbt stack, evaluating build-vs-buy tradeoffs, standardizing critical components, and deprecating legacy systems through clear, aligned design documentation.
- • Serve as the senior-most individual contributor on a 6–10 person engineering team, mentoring senior engineers through code reviews, design reviews, and hands-on problem-solving on the most complex technical challenges.
- • Partner directly with data science and product teams to translate ambiguous modeling and research requirements into precise, reliable data contracts and SLAs that enable scalable, trustworthy insights.
- • Own end-to-end incident response and post-mortems for critical data pipeline failures, transforming reactive firefighting into systemic, preventative engineering solutions.
- • Design and implement AI-driven (agentic) workflows to automate data quality validation, anomaly detection, and analytics orchestration across the data platform.
- • Influence the broader engineering organization’s data strategy by setting standards, promoting best practices, and ensuring alignment across teams on data governance, reliability, and scalability.
- • Build and maintain scalable, cost-efficient pipelines that balance throughput, latency, and operational expense while ensuring data integrity for customer-facing products and internal decision science.
- • Communicate technical tradeoffs and decisions clearly to engineering, product, and executive stakeholders through written design docs, presentations, and cross-functional collaboration.
- • Champion a culture of ownership, technical excellence, and continuous improvement, raising the bar for engineering quality across the data platform team and beyond.
🎯 Requirements
- • 10+ years of software engineering experience, with at least 4 years building production data platforms at meaningful scale (terabytes/day, hundreds of pipelines, or comparable)
- • Track record of Staff-level technical leadership: setting direction across multiple workstreams, writing design docs others build from, and mentoring senior engineers
- • Deep expertise in Python and SQL/dbt, with strong fluency in a modern orchestrator (Dagster, Airflow, Temporal, etc.) and a cloud data warehouse (BigQuery, Snowflake, etc.)
- • Demonstrated ownership of a non-trivial data platform — including schema design, schema evolution, data quality, lineage, cost, and reliability — not just writing pipelines, but designing the system the pipelines live in
- • Strong product judgment — comfortable working with data science, machine learning, or analytics consumers and translating their needs into clean data contracts
- • Excellent written and verbal communication; able to defend technical decisions to engineering, product, and exec stakeholders
🏖️ Benefits
- • Flexible PTO — take time when you need it
- • Equity — startup environment with part-ownership in company successes
- • Top-of-the-line health, dental, and vision insurance with multiple plan options
- • WFH stipend to support productive remote setup
- • Events & offsites — opportunities to connect and celebrate in person
- • Free lunch when working from office hub locations (SF, NYC, Seattle)
- • New Parent Leave — time to welcome your newest Hausmate
Skills & Technologies
See exactly how your profile matches this role — strengths, skill gaps, and what to do about them.
About Haus Technologies Inc.
Haus Technologies Inc. operates an online marketplace for buying and selling residential real estate. The platform enables homeowners to list properties, schedule tours, and receive offers without traditional agent commissions. Buyers browse listings, book self-guided showings through the app, and submit bids directly. Haus provides valuation tools, digital offer management, and transaction coordination, aiming to reduce fees and streamline the home-sale process. Founded in 2016, the company has facilitated transactions in multiple U.S. metropolitan areas while generating revenue through listing subscriptions and optional service upgrades.
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