Senior Analytics Engineer

Wispr Flow is making it as effortless to interact with your devices as talking to a close friend. Voice is the most natural, powerful way to communicate — and we’re building the interfaces to make that a reality.

Today, Wispr Flow is the first voice dictation platform people use more than their keyboards — because it understands you perfectly on the first try. It’s context-aware, personalized, and works anywhere you can type, on desktop or phone.

Dictation is just our first act. We’re building the interaction layer for your computer — a system that’s capable, understands you, and earns your trust. It will start by writing for you, then move to taking actions, and ultimately anticipate your needs before you ask.

We’re a team of AI researchers, designers, growth experts, and engineers rethinking human-computer interaction from the ground up. We value high-agency teammates who communicate openly, obsess over users, and sweat the details. We thrive on spirited debate, truth-seeking, and real-world impact.

This year, we've grown our revenue 50% month-over-month and with our latest $30M Series A, this is just the beginning.

We’re looking for a Senior Analytics Engineer to help us design, build, and scale the analytical foundation that powers insights across product, growth, and operations. You’ll work at the intersection of data engineering and analytics - transforming raw product, GTM, and finance data into clean, reliable models that enable everyone at the company to make better, faster, and data-informed decisions.

This role is highly cross-functional: you’ll partner with Product, Marketing, Growth, and Finance teams to ensure our analytics stack is robust, scalable, and purpose-built for experimentation, reporting, and machine learning.

Build the Data Foundation

• Own our dbt project—ensuring reliable, performant, well-documented data models.

• Design and maintain the ClickHouse data warehouse and ingestion processes.

• Create core entities and datasets that account for complex business processes and logic

Enable Analytics & Experimentation

• Define event tracking requirements with Product and Growth to support key KPIs.

• Build self-serve datasets powering BI dashboards, funnels, retention analyses, and lifecycle metrics.

• Model key entities and build data marts optimized for experimentation and retention.

Drive Data Quality & Automation

• Implement automated testing, validation, and observability.

• Automate dbt jobs, CI/CD, and version control.

• Create rETL pipelines to push enriched data to GTM and marketing tools.

Cross-Functional Collaboration

• Act as data liaison between Engineering, GTM, and Finance—ensuring consistent metric definitions and proper system instrumentation.

• Enable stakeholder self-service access to trusted insights.

• 5+ years of experience in analytics engineering, data engineering, or a similar role in a SaaS or product-led environment.

• Deep expertise in SQL, dbt and modern data modeling best practices.

• Proven experience working with event-based and product usage data (e.g., Posthog, Amplitude, Segment).

• Experience connecting marketing data (paid ads, campaigns, attribution) to product analytics—ideally having built end-to-end pipelines from ad platforms through to conversion and retention metrics.

• Comfortable with large-scale data systems (ClickHouse, BigQuery, Snowflake, Redshift).

• Familiarity with CI/CD, Git-based workflows, and automated testing.

• Experience collaborating cross-functionally with engineers, analysts, and product manager.

• Bonus: experience with reverse ETL, BI tool setup, or Python-based data workflows.

• A chance to shape the data foundation of a high-growth consumer SaaS product from the ground up.

• Ownership over critical infrastructure that directly impacts product decisions and business growth.

• Collaborative, data-first culture that values experimentation, transparency, and autonomy.

• Opportunity to introduce new tools, practices, and automation to evolve the analytics platform.

We consider all qualified applicants without regard to legally protected characteristics and provide reasonable accommodations upon request.

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