Senior Analytics Engineer, Product

Senior Analytics Engineer, Product

San Francisco, USA (Hybrid)

Recognized on the 2025 Forbes Cloud 100 list, Click House is one of the most innovative and fast-growing private cloud companies. With more than 3,000 customers and ARR that has grown over 250 percent year over year, Click House leads the market in real-time analytics, data warehousing, observability, and AI workloads.

The company's sustained, accelerating momentum was recently validated by a $400M Series D financing round. Over the past three months, customers including Capital One, Lovable, Decagon, Polymarket, and Airwallex have adopted the platform or expanded existing deployments. These customers join an established base of AI innovators and global brands such as Meta, Cursor, Sony, and Tesla.

We're on a mission to transform how companies use data. Come be a part of our journey!

Click House is hiring a Senior Analytics Engineer, Product, to help scale our product analytics function and turn data into a strategic asset for the teams building Click House Cloud and our broader product portfolio.

In this role, you will be a core operator of our product data system, partnering deeply with Product, Engineering, and Growth to define what we measure, how we model it, and how we use it to make better decisions. You will own foundational data models, metrics, and analytical workflows that span growth and our expanding suite of Click House products as we continue to build out our product data function.

Hybrid:
We intend to fill this role in the San Francisco Bay Area, and expect this position to go into one of our Bay Area offices, Menlo Park and San Francisco, 1-2x per week.

• Understand the data needs of stakeholder teams in terms of key data models and reporting, and translate them into technical requirements
• Develop deep expertise in the Click House product and platform, becoming the connective tissue between product surfaces, engineering telemetry, and stakeholder reporting
• Own and develop core data models, datasets, and dashboards that serve as the foundation for product decision-making across growth and the broader Click House product portfolio
• Partner closely with Product, Engineering, and Growth to align on metric definitions, instrument new features, and operationalize a single source of truth for product data
• Build scalable data systems and workflows that improve data accessibility, reliability, and usability across the organization
• Develop AI-ready data models and self-service solutions that enable natural language access and automated insights
• Deliver insights and recommendations that inform product strategy, roadmap prioritization, and growth experimentation

• 5+ years of experience in analytics engineering, BI, or data roles within a SaaS or technology company
• Deep experience supporting Product, Growth, or Engineering functions, ideally in a product-led or technical product environment
• Highly proficient in SQL and experienced in building analytical data models with dbt or similar tools
• Experience working with modern data warehouses such as Click House, Snowflake, or Big Query, and is excited to go deep on Click House
• Proficient in Python for data analysis, automation, or workflow development
• Highly fluent with AI tools and workflows, including LLMs, AI coding assistants, and automation frameworks, and applies them effectively in analytical work
• Communicates clearly and can translate complex data into actionable business insights for both technical and non-technical audiences
• Comfortable operating in ambiguity and taking ownership of open-ended problems in a fast-growing function

The typical starting salary for this role in the US is

$175,500 - $219,600 USD

The typical starting salary for this role in US Premium Markets is

$195,000 - $244,000 USD

For roles based in the United States, the typical starting salary range for this position is listed above. In certain locations, such as the San Francisco Bay Area and the New York City Metro Area, a premium market range may apply, as listed.

These salary ranges reflect what we reasonably and in good faith believe to be the minimum and maximum pay for this role at the time of posting. The actual compensation may be higher or lower than the amounts listed, and the ranges may be subject to future adjustments.

An individual's placement within the range will depend on various factors, including (but not limited to) education, qualifications, certifications, experience, skills, location, performance, and the needs of the business or organization.

If you have any questions or comments about compensation as a candidate, please get in touch with us at p

• Flexible work environment
  - Click House is a globally distributed company and remote-friendly. We currently operate in over 20 countries.
• Healthcare
  - Employer contributions towards your healthcare.
• Equity in the company
  - Every new team member who joins our company receives stock options.
• Time off
  - Flexible time off…