Manager of Analytics Engineering

Who we are

Typeform is a refreshingly different form builder. We help over 150,000 businesses collect the data they need with forms, surveys, and quizzes that people enjoy. Designed to look striking and feel effortless to fill out, Typeform drives 500 million responses every year—and integrates with essential tools like Slack, Zapier, and Hubspot.

Typeform is fully remote by design. For this role, we can hire candidates based in the ET Timezone in the US.

About the Team

At Typeform, the Data & Insights team’s charter is to make data actionable through multiple mediums—reports, dashboards, AI/ML models, and robust data infrastructure—that help us fuel growth and drive efficiencies across the business. The Analytics Engineering function plays a foundational role in this mission: designing trusted, scalable data models that power strategic insights, experimentation, and automation across the company.

About the Role

We’re looking for a Manager of Analytics Engineering. As the Analytics Engineering leader at Typeform, you’ll lead a team of analytics engineers while also staying hands-on in the work. You’ll be responsible for developing our data modeling strategy, maturing our semantic and reverse ETL layers, and enabling cross-functional teams to confidently self-serve on business-critical metrics. You’ll play a key role in shaping the future of our analytics stack and will partner closely with stakeholders across R&D and GTM to ensure our data foundation scales with the business.

What You’ll Do

Strategic Leadership & Team Development:

• Manage, mentor, and grow a team of 4–5 analytics engineers—fostering a culture of technical excellence, knowledge sharing, and continuous improvement.

• Define and prioritize the analytics engineering roadmap in partnership with stakeholders across Product, Engineering, Marketing, RevOps, and Data.

• Lead cross-functional efforts to align on core metrics, semantic layers, and taxonomy—ensuring scalable, reusable data assets across teams.

• Partner with Data Engineering to evolve our data platform and ensure pipelines are efficient, maintainable, and cost-optimized.

• Champion high standards for documentation, testing, and governance to ensure reliability and trust in our datasets.

Technical Execution & Hands-On Work:

• Own the end-to-end development of canonical data models in dbt—ensuring clarity, performance, and alignment with business needs.

• Build and maintain key data pipelines and LookML models powering dashboards, experimentation, and ML workflows.

• Contribute to the development and monitoring of operational data flows (e.g. reverse ETL pipelines via Census).

• Implement and iterate on quality controls, including dbt tests, anomaly detection, and alerting tools (e.g. Monte Carlo, Great Expectations).

• Stay current on advancements in the modern data stack and continuously improve our tooling and development workflows.

Cross-Functional Enablement & Impact:

• Translate business requirements into scalable, maintainable data solutions—enabling self-service and improving data access across the org.

• Advocate for data best practices and coach stakeholders on the effective use of our BI tools (Looker, etc.).

• Help define how success is measured through collaboration on experimentation instrumentation, analytics enablement, and metric standardization.

• Represent the Analytics Engineering function in planning cycles, vendor/tooling discussions, and cross-functional initiatives.

What You Bring

• 7+ years of experience in analytics/data engineering, with 2+ years in a team lead or management capacity.

• Deep expertise in SQL, dbt, and modeling performant data sets in modern cloud data warehouses (Snowflake, BigQuery, Redshift).

• Experience working with tools like Looker, Census, and workflow orchestrators (e.g. Airflow, Dagster).

• Familiarity with Python for scripting, automation, or orchestration tasks.

• Strong communication skills and a proven track record of cross-functional partnership and stakeholder alignment.

• A mindset of mentorship and a passion for helping others grow technically and professionally.

Extra awesome:

• You’ve led or contributed to initiatives around data governance, semantic modeling, or reverse ETL at scale.

• You’ve helped scale a data team or shaped processes for testing, CI/CD, and deployment of data models.

• Experience working with event tracking systems (e.g. Segment, Rudderstack) and supporting experimentation workflows (Amplitude, Growthbook).

• You’ve worked in a high-growth, product-led SaaS company and understand the importance of enabling fast, reliable decision-making.

No one likes a guessing game — that’s why we're transparent about the salary range for this role. In addition to the base, we offer a 5-10% bonus depending on your level and performance. The range is broad because we tailor total compensation based on your location, experience, education, and skillset.
We also want to ensure equitable pay across the team and alignment with market data — but let us handle those details. We’re committed to clarity and honesty, so feel free to ask us anything along the way.

Pay range
$170,000—$200,000 USD

*Typeform drives hundreds of millions of interactions each year, enabling conversational, human-centered experiences across the globe. We move as one team, empowering our collective efforts by valuing each individual’s unique perspective. This fosters strong bonds grounded in respect, transparency, and trust. We champion our diverse customer base by anticipating their needs and addressing their challenges with priority. Committed to excellence, we hold high expectations for ourselves and each other, continuously striving to deliver exceptional results.

We are proud to be an equal-opportunity employer. We celebrate diversity and stand firmly against discrimination and harassment of any kind—whether based on race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity or expression, or veteran status. Everyone is welcome here.