Senior Analytics Engineer, Product

ClickHouse

$175K — $219K *
Information Technology
5 - 7 years of experience
Job Overview by Ladders

Qualifications

  • 5+ years of experience in analytics engineering or data roles within a SaaS or technology company
  • Deep experience assisting Product, Growth, or Engineering functions in a product-led environment
  • Highly proficient in SQL and analytical data model building using dbt or similar tools
  • Experience with modern data warehouses like ClickHouse, Snowflake, or BigQuery
  • Proficient in Python for data analysis and automation
  • Fluent with AI tools, including LLMs and automation frameworks
  • Strong communicator, capable of simplifying complex data insights for diverse audiences

Responsibilities

  • Understand stakeholder data needs and translate them into technical requirements
  • Develop expertise in ClickHouse products to enhance reporting and decision-making
  • Own and build foundational data models and dashboards for product strategy
  • Collaborate with teams to align on metric definitions and operationalize data
  • Construct scalable data systems to enhance data accessibility and reliability
  • Create AI-ready data models and solutions for automated insights
  • Deliver actionable insights to impact product strategy and growth experimentation

Benefits

  • Flexible work environment with remote-friendly policies
  • Employer contributions towards healthcare expenses
  • Stock options provided to every new team member
  • Flexible time off policy in the US with generous entitlements in other regions
  • $500 allowance for home office setup for remote employees
  • Opportunities for in-person connections during global company gatherings
Full Job Description
ClickHouse 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 ClickHouse 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 ClickHouse 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 our Menlo Park office 1-2x per week. What You'll Be Doing: • 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 ClickHouse 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 ClickHouse 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 What You Bring Along: • 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 ClickHouse, Snowflake, or BigQuery, and is excited to go deep on ClickHouse • 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 Compensation 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 [redacted]. Perks • Flexible work environment - ClickHouse 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 in the US, generous entitlement in other countries. • A $500 Home office setup if you're a remote employee. • Global Gatherings - We believe in the power of in-person connection and offer opportunities to engage with colleagues at company-wide offsites.

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