Jobs at Haus.io

Build and maintain backend services, APIs, data pipelines, workflows, and scripts that automate customer data ingestion and validation. Develop distributed data platform systems integrating ad networks, warehouses, and partner tools; contribute to AI services; collaborate with Customer Success on customer data models; and participate in on-call support.

Own the strategy and execution of Haus’s enterprise demand generation engine. Responsibilities include defining ICP and segmentation, developing ABM programs, managing paid, content, email, events, webinars, and sponsorships, and partnering with Sales and Product Marketing. The role owns pipeline targets, budget, attribution, funnel reporting, and performance measurement while managing one direct report and agency relationships. This hands-on position builds demand generation infrastructure and repeatable enterprise pipeline from the ground up.

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.

Lead end-to-end development and productionization of machine learning systems for causal marketing measurement and optimization, especially cMMM. Build probabilistic and statistical libraries, maintain ML pipelines, implement agentic AI workflows and model validation, review designs and code, collaborate cross-functionally, and mentor ML engineers.

Own marketing measurement models for multiple customers, partnering with strategy managers from kickoff through model release, interpretation, enablement, and action planning. Configure and QA model inputs and outputs, manage escalations, deliver deep-dive analyses and scenario work, and support renewals and account growth. Build scalable playbooks, documentation, and AI-assisted workflows while translating complex measurement results into actionable budgeting and campaign decisions. Provide customer feedback to product, science, and engineering teams and support pre-sales and case studies.

Manage a portfolio of customers to design, run, and interpret marketing experiments; translate learnings into budget and strategy decisions; advise on best practices; build stakeholder relationships; partner with Product/Science/Engineering to scale solutions; produce playbooks and support renewals and expansion.