Haus (madeinhaus.com)

Haus (madeinhaus.com)

Staff Engineer - Data Platform - San Francisco

San Francisco, CA · Staff+

Sponsorship not specifiedDetected 40 days ago
PythonCode ReviewSQLBigQuerySnowflakeGCPTemporalMachine LearningSparkAirflowdbtData EngineeringData ScienceAgentic AIIncident ResponseResearchLeadershipCommunicationCollaborationMentoring

About the role

  • 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.

Responsibilities

  • Be 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.
  • Design and lead implementation of high-leverage systems: schema evolution, data contracts, DQ frameworks, idempotent backfills, lineage, time-travel, data reproducibility and pipeline observability.
  • Drive 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.
  • Raise the engineering bar through code review, design review, and mentorship
  • Partner with data science to translate fuzzy modeling and research needs into pipeline contracts and SLAs that downstream teams can trust.
  • Own incident response and post-mortems for critical pipeline failures
  • Drive design and implementation of AI (Agentic) workflows for data quality and analytics
  • Raise the engineering bar through code review, design review, and mentorship; level up Senior engineers and unblock the team on the hardest problems.
  • Own incident response and post-mortems for critical pipeline failures; turn one-off fires into systemic fixes.
  • 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.

Requirements

  • 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).
  • 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.
  • Demonstrated 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.
  • Strong product judgment - comfortable working with DS, ML, 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.
  • Bonus Points
  • Background contributing to or maintaining open-source data tooling/frameworks (Apache Spark, Apache Beam, Apache Iceberg).
  • Experience building AI Agents in a data platform setting.

Skills

  • Influence the broader engineering org's data strategy.

Compensation

  • Haus 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.
  • With a founding team of former product managers, economists, and engineers from Google, Netflix, Meta, and Amazon, we make high-quality decision science, incrementality testing, and causal marketing mix modeling accessible to businesses of all sizes-automating the heavy lifting of experiment design, data processing, and insights generation.
  • Haus works with leading brands like FanDuel, Sonos, and Dr.

Benefits

  • 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
  • New Parent Leave - take time to welcome your newest Hausmate
  • 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.

Company info

  • Haus'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 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.

Equal opportunity

  • equal opportunity employer.
  • Haus is an equal opportunity employer.
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