Make smarter enterprise marketing investments with Haus’ AI-powered causal marketing platform and expert guidance. Backed by Insight.
About the role
This backend role is centered on developing workflows to help customers connect their data and to configure the ingestion of that data with little to no human intervention. You will be a key part of the onboarding experience for customers as well as Haus’s efforts to scale and efficiently service an ever-expanding customer base.
What they're looking for
- 5+ years experience building backend services & APIs (backend Engineer, full stack engineer, data engineer or similar)
- Proficiency in Python and SQL/dbt, with strong fluency in a modern orchestrator (Dagster, Airflow, Temporal, etc)
- Experience with cloud data lakehouse/warehouse (BigQuery, Databricks, etc)
- Experience with cloud infrastructure: Google Cloud, AWS
- You're passionate about automating data ingestion and processing workflows
- You're equally strong at backend engineering: production services, APIs, distributed systems
More about this role
Haus is the causal marketing platform top businesses trust to optimize billions in ad spend worldwide. With support from PhD economists, data scientists, and growth experts, Haus’ AI-driven technology translates complex marketing measurement into clear action and outcomes, enabling brands like Dyson, Wayfair, Sonos, Fanduel, SharkNinja, and Intuit to optimize spend, accelerate growth, and make smarter marketing decisions at scale.
This backend role is centered on developing workflows to help customers connect their data and to configure the ingestion of that data with little to no human intervention. You will be a key part of the onboarding experience for customers as well as Haus’s efforts to scale and efficiently service an ever-expanding customer base.
The Data Onboarding team is part of Haus's Data Platform, which powers the entire incrementality platform: every causal experiment, every marketing mix model, every dollar of ad spend we help customers reallocate runs on systems this team builds. Under the hood, that platform is a set of distributed backend services — ingestion from dozens of ad-network APIs, customer warehouses, and partner tools; normalization and validation...
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