{"schemaVersion":"jobsearcher.job.v1","id":"2be83acd8917b61fb4c1a534","url":"https://jobsearcher.com/jobs/2be83acd8917b61fb4c1a534","canonicalUrl":"https://jobsearcher.com/jobs/2be83acd8917b61fb4c1a534","title":"Staff Engineer - Data Platform","description":"About Haus\nHaus is the incrementality platform leading brands trust to optimize billions in ad spend worldwide. Using frontier causal inference-based econometric models to run experiments, we help brands measure the business impact of marketing, pricing, and promotions with scientific precision. Over $360B is spent annually on paid advertising in the US alone, and the famous quote “half the money I spend on advertising is wasted; the trouble is I don't know which half” still rings true. Haus helps marketers identify which half, and reallocate it to maximize growth.\n\nThe Role\nHaus's data engineering team powers the entire incrementality platform — every causal experiment, every marketing mix model, every dollar of ad spend we help our customers reallocate runs on the pipelines this team builds. We are looking for a Staff Software Engineer to set the technical direction for how Haus ingests data from ad networks, customer warehouses, and partner tools, and how we normalize it into a clean, trustworthy foundation for our data science research and customer-facing products. You will be the senior‑most IC on a 6‑10 person team, partnering directly with engineering leadership, data science, and product teams to make Haus's data platform a durable competitive advantage.\n\nWhat you’ll do\n\nBe the tech‑lead and architect for Haus's data ingestion and normalization platform — ad network APIs (Google, Meta, TikTok, Amazon, etc.), Fivetran connectors, and customer warehouses (Snowflake, BigQuery) — balancing throughput, cost, and reliability.\n\nDesign and lead implementation of high‑leverage systems: schema evolution, data contracts, DQ frameworks, idempotent backfills, lineage, time‑travel, data reproducibility and pipeline observability.\n\nDrive architectural decisions in our GCP / BigQuery / dbt stack — build vs. buy, what to standardize, what to deprecate — and write the design docs that align Engineering, DS, and Product teams.\n\nRaise the engineering bar through code review, design review, and mentorship; level up Senior engineers and unblock the team on the hardest problems.\n\nPartner with data science to translate fuzzy modeling and research needs into pipeline contracts and SLAs that downstream teams can trust.\n\nOwn incident response and post‑mortems for critical pipeline failures; turn one‑off fires into systemic fixes.\n\nDrive design and implementation of AI (Agentic) workflows for data quality and analytics.\n\nInfluence the broader engineering org's data strategy.\n\nQualifications\n\n8‑10+ years of software engineering experience, with at least 4 years building production data platforms at meaningful scale (terabytes/day, hundreds of pipelines, or comparable).\n\nTrack record of Staff‑level technical leadership: setting direction across multiple workstreams, writing design docs others build from, and mentoring senior engineers.\n\nDeep 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.).\n\nDemonstrated ownership of a non‑trivial data platform — schema design, schema evolution, data quality, lineage, cost, and reliability — not just writing pipelines, but designing the system the pipelines live in.\n\nStrong product judgment — comfortable working with DS, ML, or analytics consumers and translating their needs into clean data contracts.\n\nExcellent written and verbal communication; able to defend technical decisions to engineering, product, and exec stakeholders.\n\nBonus Points\n\nBackground contributing to or maintaining open‑source data tooling/frameworks (Apache Spark, Apache Beam, Apache Iceberg).\n\nExperience building AI Agents in a data platform setting.\n\nWhat We Offer\nWe’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.\n\nIf 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.\n\nWe work in small, mission‑driven teams that prioritize inclusion, collaboration, and growth over hierarchy or red tape.\n\nSome of our benefits include:\n\nFlexible PTO - take time when you need it!\n\nEquity – Startup environment with part‑ownership in our successes\n\nTop of the line health, dental, and vision insurance - multiple plan options so you can pick what fits you best\n\nWFH stipend to support the set up you need to be productive\n\nEvents & Offsites – opportunities to connect and celebrate in real life!\n\nFree Lunch – Grab a bite on us when you choose to work from the office (hub locations include SF, NYC and Seattle)\n\nNew Parent Leave – take time to welcome your newest Hausmate\n\nWe 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.\n\nEqual Opportunity Employment\nHaus 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.\n\nWe 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.\n\n#J-18808-Ljbffr","company":"Haus Analytics","rawCompany":"haus analytics","city":"Millbrae","state":"CA","isRemote":false,"isActive":false,"createdAt":"2026-06-20T04:55:30.230Z","occupations":[{"code":"15-1243.01","title":"Data Warehousing Specialists","slug":"data-warehousing-specialists"},{"code":"15-1252.00","title":"Software Developers","slug":"software-developers"},{"code":"15-2051.00","title":"Data Scientists","slug":"data-scientists"}],"industries":[{"code":"513210","title":"Software Publishers","slug":"software-publishers"},{"code":"541512","title":"Computer Systems Design Services","slug":"computer-systems-design-services"},{"code":"541511","title":"Custom Computer Programming Services","slug":"custom-computer-programming-services"}],"jobPosting":{"@context":"https://schema.org","@type":"JobPosting","title":"Staff Engineer - Data Platform","description":"About Haus\nHaus is the incrementality platform leading brands trust to optimize billions in ad spend worldwide. Using frontier causal inference-based econometric models to run experiments, we help brands measure the business impact of marketing, pricing, and promotions with scientific precision. Over $360B is spent annually on paid advertising in the US alone, and the famous quote “half the money I spend on advertising is wasted; the trouble is I don't know which half” still rings true. Haus helps marketers identify which half, and reallocate it to maximize growth.\n\nThe Role\nHaus's data engineering team powers the entire incrementality platform — every causal experiment, every marketing mix model, every dollar of ad spend we help our customers reallocate runs on the pipelines this team builds. We are looking for a Staff Software Engineer to set the technical direction for how Haus ingests data from ad networks, customer warehouses, and partner tools, and how we normalize it into a clean, trustworthy foundation for our data science research and customer-facing products. You will be the senior‑most IC on a 6‑10 person team, partnering directly with engineering leadership, data science, and product teams to make Haus's data platform a durable competitive advantage.\n\nWhat you’ll do\n\nBe the tech‑lead and architect for Haus's data ingestion and normalization platform — ad network APIs (Google, Meta, TikTok, Amazon, etc.), Fivetran connectors, and customer warehouses (Snowflake, BigQuery) — balancing throughput, cost, and reliability.\n\nDesign and lead implementation of high‑leverage systems: schema evolution, data contracts, DQ frameworks, idempotent backfills, lineage, time‑travel, data reproducibility and pipeline observability.\n\nDrive architectural decisions in our GCP / BigQuery / dbt stack — build vs. buy, what to standardize, what to deprecate — and write the design docs that align Engineering, DS, and Product teams.\n\nRaise the engineering bar through code review, design review, and mentorship; level up Senior engineers and unblock the team on the hardest problems.\n\nPartner with data science to translate fuzzy modeling and research needs into pipeline contracts and SLAs that downstream teams can trust.\n\nOwn incident response and post‑mortems for critical pipeline failures; turn one‑off fires into systemic fixes.\n\nDrive design and implementation of AI (Agentic) workflows for data quality and analytics.\n\nInfluence the broader engineering org's data strategy.\n\nQualifications\n\n8‑10+ years of software engineering experience, with at least 4 years building production data platforms at meaningful scale (terabytes/day, hundreds of pipelines, or comparable).\n\nTrack record of Staff‑level technical leadership: setting direction across multiple workstreams, writing design docs others build from, and mentoring senior engineers.\n\nDeep 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.).\n\nDemonstrated ownership of a non‑trivial data platform — schema design, schema evolution, data quality, lineage, cost, and reliability — not just writing pipelines, but designing the system the pipelines live in.\n\nStrong product judgment — comfortable working with DS, ML, or analytics consumers and translating their needs into clean data contracts.\n\nExcellent written and verbal communication; able to defend technical decisions to engineering, product, and exec stakeholders.\n\nBonus Points\n\nBackground contributing to or maintaining open‑source data tooling/frameworks (Apache Spark, Apache Beam, Apache Iceberg).\n\nExperience building AI Agents in a data platform setting.\n\nWhat We Offer\nWe’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.\n\nIf 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.\n\nWe work in small, mission‑driven teams that prioritize inclusion, collaboration, and growth over hierarchy or red tape.\n\nSome of our benefits include:\n\nFlexible PTO - take time when you need it!\n\nEquity – Startup environment with part‑ownership in our successes\n\nTop of the line health, dental, and vision insurance - multiple plan options so you can pick what fits you best\n\nWFH stipend to support the set up you need to be productive\n\nEvents & Offsites – opportunities to connect and celebrate in real life!\n\nFree Lunch – Grab a bite on us when you choose to work from the office (hub locations include SF, NYC and Seattle)\n\nNew Parent Leave – take time to welcome your newest Hausmate\n\nWe 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.\n\nEqual Opportunity Employment\nHaus 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.\n\nWe 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.\n\n#J-18808-Ljbffr","datePosted":"2026-06-20T04:55:30.230Z","dateModified":"2026-06-20T04:55:30.230Z","hiringOrganization":{"@type":"Organization","name":"Haus Analytics","sameAs":"https://jobsearcher.com"},"jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"Millbrae","addressRegion":"CA","addressCountry":"US"}},"identifier":{"@type":"PropertyValue","name":"JobSearcher","value":"2be83acd8917b61fb4c1a534"},"url":"https://jobsearcher.com/jobs/2be83acd8917b61fb4c1a534"}}