Senior Software Engineer, Data Platform

Senior Software Engineer, Data Platform About Haus 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 https://www.linkedin.com/pulse/linkedin-top-startups-2025-50-us-companies-rise-linkedin-news-hox6f/! What you'll do: This is a unique opportunity to help us build robust and scalable systems and services that handle data workloads at Haus. The Data Platform includes systems that power the Haus product and are at the heart of what we do. The ideal candidate is somebody who loves working with data, is a great software engineer, and an excellent communicator. You will design, scale, and maintain the systems that support the Haus platform and enable data-driven decision-making at Haus. Responsibilities - Build data solutions on top of Google Cloud Platform (GCP) using Python and other languages as appropriate. - Contribute to the technical direction and development of Haus’ data services, infrastructure and tools. - Create and maintain scalable data pipelines and foundational datasets to support analytics, modeling, experimentation, and product/business needs. - Develop and support data quality checks at scale, implementing alerting and anomaly detection as necessary - Create dashboards and reports to support business objectives and enable data-driven decision making - Partner with data scientists, engineers, and product teams to accomplish all of the above! Qualifications - 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. Bonus points - 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. What we offer We’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. 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. If you're looking for predictability or rigid structure or you prefer order-taking to go-getting, ... (truncated, view full listing at source)