Senior Manager Analytics Engineering

Typeform is fully remote by design. For this role we can hire candidates based in the US UK Ireland Germany Spain Portugal or the Netherlands.

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 or Senior Manager of Analytics Engineering —and we’re flexible on level for the right candidate. Whether you’re a seasoned senior manager or a strong manager ready to level up we’d love to meet you.

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 (50-60%)

• 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 (20-30%)

• 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 (20-30%)

• 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

$170000—$240000 USD