Senior Software Engineer, Data Platform

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. Squatch, delivering ROI gains as high as 30x.

Haus is well-capitalized and backed by top-tier VCs, including Insight Partners, Baseline Ventures, Haystack, and others. We're honored that Haus has once again been recognized by LinkedIn as a 2025 Top Startup!

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  Build data solutions on top of Google Cloud Platform (GCP) using Python and other languages as appropriate.

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  Contribute to the technical direction and development of Haus’ data services, infrastructure and tools.

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  Create and maintain scalable data pipelines and foundational datasets to support analytics, modeling, experimentation, and product/business needs.

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  Develop and support data quality checks at scale, implementing alerting and anomaly detection as necessary

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  Create dashboards and reports to support business objectives and enable data-driven decision making

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  Partner with data scientists, engineers, and product teams to accomplish all of the above!

• 4-7+ years of experience as a Software Engineer.

• Experience building and deploying large-scale distributed systems in Python or Go: it makes you uncomfortable deploying something for end-users without thinking about things like performance metrics, monitors and dashboards, graceful degradation and feature flags.

• Experience with cloud infrastructure (Google Cloud, AWS, etc).

• Experience building ETL/ELT data pipelines - batch and realtime

• Experience working with SQL and NoSQL databases.

• Earlier stage startup experience.

• Experience with data warehouses: Snowflake, BigQuery, RedShift.

• Experience with data workflows and tools: dbt, dagster.

• Experience with Third party data APIs integrations

• Experience with build systems and infrastructure management tooling like Terraform. 

• BS/MS/PhD in Computer Science, Applied Mathematics or a related field.