Senior Data Analyst II

Compass•Seattle, WA

5d•$138,000 - $153,000

About The Position

The Senior Data Analyst II will serve as the analytical partner to Compass’s Product organization, working on the central Data & Analytics team to understand how agents, their clients, and consumers engage with the platform. The role supports product and investment decisions by identifying what is working, what is not, and opportunities or risks that may not yet be visible. The analyst will work with platform data in the company’s lakehouse and collaborate with Analytics Engineering, Analytics, and Data Engineering to establish trusted, governed metrics and reliable product data.

Requirements

At least 5 years of experience in analytics, including significant product or behavioral analytics experience with funnels, cohorts, retention, and engagement segmentation.
Advanced SQL and Python skills.
Hands-on experience shaping and querying raw event or clickstream data.
Experience validating telemetry, auditing event tracking, and partnering with engineering teams to resolve data discrepancies before metrics reach decision-makers.
Ability to develop a clear point of view on what matters to users and the business.
Ability to make sound, defensible claims from observational data and clearly explain its limitations.
Track record of influencing decisions with senior product leaders and communicating complex analyses concisely, including findings stakeholders may not want to hear.
Accountability for outcomes and experience guiding junior analysts.

Nice To Haves

Experience with Heap, Segment, Amplitude, or similar event analytics tools.

Responsibilities

Own analysis of agent, client, and consumer product engagement, including adoption, depth, retention, and relationships between engagement across groups.
Partner with Product Leadership on roadmap and investment decisions by framing options and trade-offs.
Identify user behavior, engagement risks, and adoption opportunities, and provide evidence-based recommendations.
Define success metrics before product launches and assess impact afterward using cohort, pre/post, and other observational methods when controlled experiments are unavailable.
Use lakehouse platform data to prototype engagement metrics and partner with Analytics Engineering to establish governed, reusable metric definitions.
Partner with Analytics and Data Engineering to define tracking standards, identify telemetry gaps, and help prioritize product analytics requests.
Mentor junior data analysts in scoping, analytical methods, and stakeholder partnership.
Communicate complex analyses as concise executive narratives and present findings to senior product leaders.