Haus Analytics

Title: Staff Engineer - Data Platform Location: San Francisco United States Location San Francisco, CA; Seattle, WA Employment Type Full time Location Type Hybrid Department Engineering Compensation - $240K – $260K Salary ranges are determined by role and level, and within the range individual pay is determined by additional factors including job-related skills, experience, and relevant education or training. Please note that the compensation details listed in this job posting reflect the base salary only, and do not include equity or benefits. Job Description: 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! The Role Haus's data engineering team powers the entire incrementality platform - every causal experiment, every marketing mix model, every dollar of ad spend we help our customers reallocate runs on the pipelines this team builds. We are looking for a Staff Software Engineer to set the technical direction for how Haus ingests data from ad networks, customer warehouses, and partner tools, and how we normalize it into a clean, trustworthy foundation for our data science research and customer-facing products. You will be the senior-most IC on a 6-10 person team, partnering directly with engineering leadership, data science, and product teams to make Haus's data platform a durable competitive advantage. What you'll do - Be the tech-lead and architect for Haus's data ingestion and normalization platform - ad network APIs (Google, Meta, TikTok, Amazon, etc.), Fivetran connectors, and customer warehouses (Snowflake, BigQuery) - balancing throughput, cost, and reliability. - Design and lead implementation of high-leverage systems: schema evolution, data contracts, DQ frameworks, idempotent backfills, lineage, time-travel, data reproducibility and pipeline observability. - Drive architectural decisions in our GCP / BigQuery / dbt stack - build vs. buy, what to standardize, what to deprecate - and write the design docs that align Engineering, DS, and Product teams. - Raise the engineering bar through code review, design review, and mentorship; level up Senior engineers and unblock the team on the hardest problems. - Partner with data science to translate fuzzy modeling and research needs into pipeline contracts and SLAs that downstream teams can trust. - Own incident response and post-mortems for critical pipeline failures; turn one-off fires into systemic fixes. - Drive design and implementation of AI (Agentic) workflows for data quality and analytics - Influence the broader engineering org's data strategy. Qualifications - 8-10+ years of software engineering experience, with at least 4 years building production data platforms at meaningful scale (terabytes/day, hundreds of pipelines, or comparable). - Track record of Staff-level technical leadership: setting direction across multiple workstreams, writing design docs others build from, and mentoring senior engineers. - Deep expertise in Python and SQL/dbt, with strong fluency in a modern orchestrator (Dagster, Airflow, Temporal, etc) and a cloud data warehouse (BigQuery, Snowflake, etc). - Demonstrated ownership of a non-trivial data platform - schema design, schema evolution, data quality, lineage, cost, and reliability - not just writing pipelines, but designing the system the pipelines live in. - Strong product judgment - comfortable working with DS, ML, or analytics consumers and translating their needs into clean data contracts. - Excellent written and verbal communication; able to defend technical decisions to engineering, product, and exec stakeholders. Bonus Points - Background contributing to or maintaining open-source data tooling/frameworks (Apache Spark, Apache Beam, Apache Iceberg). - Experience building AI Agents in a data platform setting. What We Offer: R&D Roles: 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, we're probably not the right fit - and that's okay. We work in small, mission-driven teams that prioritize inclusion, collaboration, and growth over hierarchy or red tape. Some of our benefits include: - Flexible PTO - take time when you need it! - Equity - Startup environment with part-ownership in our successes - Top of the line health, dental, and vision insurance - multiple plan options so you can pick what fits you best - WFH stipend to support the set up you need to be productive - Events & Offsites - opportunities to connect and celebrate in real life! - Free Lunch - Grab a bite on us when you choose to work from the office (hub locations include SF, NYC and Seattle) - New Parent Leave - take time to welcome your newest Hausmate We value in-person collaboration at Haus and give preference to candidates within commuting distance of our offices in San Francisco, Seattle, and New York City. Haus is an equal opportunity employer. We make hiring decisions without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, age, disability, veteran status, or any other protected status. We believe diverse perspectives make us stronger and are committed to an inclusive culture where everyone feels seen, heard, and empowered to contribute. Bring your authentic self - we would love to hear from you.

Title: Senior Full Stack Engineer Location: San Francisco, CA, Seattle, WA, New York City Compensation $200K – $220K Salary ranges are determined by role and level, and within the range individual pay is determined by additional factors including job-related skills, experience, and relevant education or training. Please note that the compensation details listed in this job posting reflect the base salary only, and do not include equity or benefits. Job Description: 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. The Role You’ll build and evolve the systems that power how the world’s leading brands understand the true impact of their marketing spend. Our platform runs geo-based experiments, integrates with major ad platforms (Meta, Google, TikTok), and delivers causal inference results that directly drive budget decisions worth millions of dollars. This is a full stack role where you’ll work across a Python/Flask API, a React frontend, and the data pipelines and integrations that connect them. You'll hit the ground running on a production system with real customers, shipping work that compounds in impact over time. The engineers who thrive here are the ones who can look at a mature codebase, see the path to making it better, and execute without needing to rewrite everything first. We’re also a team that leans into AI-assisted development as a genuine force multiplier — not as a novelty. Our engineers use tools like Claude Code and Cursor to move faster, generate boilerplate, accelerate exploratory work, and ship features that would have taken weeks in days. We’re looking for someone who’s excited about this way of working and wants to push the boundary of what a small, high-output engineering team can deliver. What you’ll do - Own features end-to-end: from API design and database migrations through React UI and data visualization, all the way to monitoring and on-call support - Build and harden integrations with third-party ad platforms (Meta, Google, TikTok) — design for reliability across APIs you don’t control - Evolve and modernize a production Flask + React application that serves hundreds of customers — improve architecture incrementally while shipping continuously - Design and build data-rich UIs: charts, dashboards, and interactive tools that help marketers understand complex experimental results - Collaborate closely with scientists and data engineers to translate statistical outputs into product experiences customers can act on - Use AI development tools as part of your daily workflow to accelerate delivery, explore solutions, and raise the ceiling on what you can ship - Participate in on-call rotation and own the operational health of the systems you build - Review code across the team and help set the bar for quality, clarity, and maintainability Qualifications - 5–10+ years of experience building and shipping production web applications and APIs - Strong across the full stack: you can build a well-structured API endpoint, write a database migration, and implement the frontend that consumes it - Proficiency in Python and React (or strong equivalents with willingness to ramp); experience with Flask, SQLAlchemy, or similar frameworks is a plus - Experience working in and improving large, established codebases — you’ve navigated legacy systems, made pragmatic tradeoffs between refactoring and shipping, and left things better than you found them - Comfort with cloud-native environments (GCP preferred): you understand how to deploy, monitor, and operate services in production - Experience with relational databases (MySQL/PostgreSQL) and data-heavy applications - Track record of working effectively with AI development tools (Claude, Cursor, Copilot, or similar) — you’ve integrated them into your workflow and can articulate how they change the way you build software - Strong product sense: you think about what customers need, not just what the ticket says - Excellent communication skills — you can explain technical tradeoffs clearly and work effectively with scientists, product managers, and other engineers For Staff level, we also look for: - Demonstrated ability to lead technical direction for a system or product area, making architectural decisions that hold up as the team and product scale - Experience driving cross-team or cross-system initiatives — you’ve coordinated changes across multiple services or repositories and managed the sequencing - A track record of mentoring other engineers and raising the technical bar of the team through code review, design guidance, and leading by example - Comfort operating with ambiguity: you can take a loosely defined problem, break it down, build the plan, and drive it to completion without heavy oversight Bonus Points - Earlier stage startup experience - Experience with ad platform APIs (Meta Marketing API, Google Ads API) - Experience with data visualization or experimentation platforms — if you’ve built charts that help people understand data or worked on systems that run experiments, you’ll ramp faster here - Experience with third-party data integrations and ETL workflows What We Offer: R&D Roles: 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, we’re probably not the right fit — and that’s okay. We work in small, mission-driven teams that prioritize inclusion, collaboration, and growth over hierarchy or red tape. Some of our benefits include: - Flexible PTO - take time when you need it! - Equity – Startup environment with part-ownership in our successes - Top of the line health, dental, and vision insurance - multiple plan options so you can pick what fits you best - WFH stipend to support the set up you need to be productive - Events & Offsites – opportunities to connect and celebrate in real life! - Free Lunch – Grab a bite on us when you choose to work from the office (hub locations include SF, NYC and Seattle) - New Parent Leave – take time to welcome your newest Hausmate We value in-person collaboration at Haus and give preference to candidates within commuting distance of our offices in San Francisco, Seattle, and New York City. Haus is an equal opportunity employer. We make hiring decisions without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, age, disability, veteran status, or any other protected status. We believe diverse perspectives make us stronger and are committed to an inclusive culture where everyone feels seen, heard, and empowered to contribute. Bring your authentic self — we would love to hear from you.

• Co-design experimentation roadmaps with customers, considering their media plan and operating goals • Shepherd customers through the entire experimentation process, from design to implementation, interpretation, and action steps • Advise customers on best practices to maximize value and ROI from the platform • Serve as a trusted partner on interpretation of test results and how to take action • Identify risks or escalations and manage those with a complete ownership mentality • Create collateral, resources, playbooks, and workflows that balance quality of service with designing for scale • Partner with Product, Science, & Engineering teams to translate customer requests into scalable product features • Own customer renewals and identify qualified cross-sell opportunities

• 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!

• Providing technical demonstrations of the Haus product to prospective customers • Answering technical questions about the product and serving as a subject matter expert • Creating tailored presentations and navigating competitive pitches • Building testing roadmaps that will deliver value to customers during their initial time on the platform • Conducting feasibility analyses to ensure we’ll be able to deliver value for prospective customers • Delivering feedback to the product team and representing our prospective customers’ needs in internal discussions • Attending conferences and events in order to generate pipeline • Staying current with industry trends and best practices in marketing measurement to continuously improve processes and outcomes

• Lead and develop the Account Management team • Hire, onboard, coach, and retain a team of 4–6 Account Managers. Set clear expectations, run regular 1:1s and pipeline reviews, and create an environment where AMs do the best work of their careers. • Own the team's aggregate quota for retention, gross renewal rate, and expansion (including cMMM upsells and future product launches). You are accountable for the number. • Design and implement the operating model for Account Management at Haus: account planning frameworks, renewal and expansion playbooks, QBR/EBR templates, health scoring, and forecasting cadences. • Establish clear rules of engagement between Account Management, Measurement Strategy, Sales, CX, and Product — ensuring customers experience a coordinated, high-quality Haus team. • Maintain direct involvement in the team's highest-stakes renewals, expansions, and escalations. Know when to coach from behind and when to step into the room. • Work hand-in-hand with Measurement Strategy leadership to ensure AMs and their MS counterparts operate as true account teams — sharing context, aligning on priorities, and presenting a unified front to customers. • Collaborate with Sales leadership on handoff processes, territory design, and GTM planning. Partner with Product and CX to bring customer feedback into the roadmap and service model. • Maintain accurate forecasts, pipeline views, and account health dashboards. Provide Sales and company leadership with clear, reliable visibility into renewal and expansion performance. • Use data to identify trends, risks, and opportunities across the book — and translate those insights into team-wide actions.

• Partner with engineering teams to build and deploy causal models into production at scale • Leverage existing literature and develop new science in the causal marketing measurement space • Help drive product roadmap by clearly advocating for rigorous scientific solutions to customer pain points

• Build and operate Haus’s integrated campaign engine across digital, lifecycle, and account-based programs. • Plan and execute integrated campaigns including report launches, webinar programs, account-based plays, field event amplification, and nurture programs. • Partner with Product Marketing and Content to turn launches and assets into full-funnel campaigns. • Coordinate with Sales and SDR teams on targeted account programs and outbound-supported campaigns. • Design and execute lifecycle programs including nurture sequences and re-engagement campaigns. • Partner with paid media agencies to brief campaigns and ensure paid programs support broader campaign goals. • Track campaign performance and optimize programs based on pipeline generation, meeting creation, and campaign ROI.

• Own enterprise client relationships end to end, serving as the primary point of contact for senior stakeholders, including growth leaders, analytics leaders, and data science teams; ensure satisfaction, retention, and expansion across your portfolio. • Partner closely with client data scientists as day-to-day counterparts, aligning on experiment design, data pipelines/requirements, and interpretation standards to accelerate time-to-insight and decision-making. • Co-design experimentation roadmaps with customers that reflect their media strategy, operating goals, and test capacity; guide them toward continuous experimentation programs. • Shepherd the full experimentation lifecycle — from hypothesis and design to implementation, QA, readout, and action planning — translating technical findings into clear, executive-ready recommendations. • Advise on measurement methodologies, best practices, and trade-offs — including MMM calibration and cross-system alignment — helping customers connect business questions with Haus product capabilities within their broader measurement stack. • Identify risks early and manage escalations with full ownership, while orchestrating the right internal Haus resources to drive resolution. • Systematize excellence by creating collateral, playbooks, and workflows that balance quality with scale; contribute to team knowledge-sharing and coaching.

• Initially lead multiple customer engagements end-to-end, from data onboarding to model interpretation, supporting clients to use our app, preparation of client-facing materials and action planning (i.e. translating cMMM results to planning improvements) • Build the processes, playbooks, and workflows that will eventually enable Haus' Measurement Strategy Team to take over as MMM customers' primary point of contact and serve our customers with a truly integrated suite of growth intelligence products • Manage complex data onboarding from intake to validation, working closely with customers and internal teams to ensure all datasets—no matter how messy—are thoroughly vetted and formatted for seamless ingestion into the Haus model, proactively troubleshooting and resolving anomalies as they arise • Assist in gathering customer requirements and feedback to support the MMM model design and iteration process, liaising with the Haus data science team • Explain technical concepts like multicollinearity, uncertainty, and causality to customers to help drive value through understanding MMM features and limitations • Gather and relay customer feedback to our product, science, and engineering teams to contribute to the development of scalable product features • Contribute to building scaled cMMM support by informing and implementing a long-term strategy to support customers as a part of our scalable software roadmap