Teams at Haus.io

Design and lead backend services and data pipelines for Haus’s data platform, including high-throughput ingestion, distributed systems, normalization, orchestration, data contracts, warehouse and lakehouse modeling, dbt architecture, data quality, lineage, observability, and BigQuery optimization. Set technical direction, establish engineering standards, mentor senior engineers, and collaborate with engineering, product, and data science leadership.

Design and lead backend services and data pipelines for Haus’s data platform, including high-throughput ingestion, normalization, orchestration, distributed systems, warehouse modeling, dbt architecture, data quality, lineage, and BigQuery optimization. Set technical standards for testing, APIs, observability, and CI/CD; guide architecture across the GCP stack; mentor engineers; and influence company-wide data strategy while partnering with engineering, product, and data science teams.

Leads end-to-end development and productionization of machine learning systems for causal marketing measurement and optimization, especially cMMM. Implements probabilistic and statistical methods, builds reusable ML libraries and pipelines, collaborates across engineering, product, and science teams, reviews designs and code, develops agentic ML workflows, and mentors machine learning engineers.