Data Analyst, Operations

Rocket Money•Phoenix, WA

About The Position

Rocket Money is hiring a Data Analyst to deepen the Data Analytics team’s partnership with Operations and Customer Support. The analyst will bring a strong point of view to operational problems by shaping measurement and reporting, leading ad hoc investigations, and delivering actionable insights that help improve member outcomes. The Data Analytics team works in a semi-embedded structure. Analysts build analytics tooling, use data to inform business decisions and strategy, assess experiments, and collaborate with analytics engineering and data science across product delivery, operations, finance, and marketing. The role partners with operations and customer support management, owns complex analytical work end-to-end, and helps stakeholders use data and analytics tools effectively. The tech stack includes BigQuery, dbt, Looker, Amplitude, and Deepnote.

Requirements

At least 4 years of experience in data analytics.
Proven experience working with operations teams to drive meaningful product improvements.
Advanced SQL skills.
Experience with a business intelligence tool such as Looker, Tableau, Databricks, or Power BI.
Strong expertise in data analytics and understanding of data systems and processes, particularly scalable, repeatable self-service analytics.
Strong stakeholder management skills and ability to build effective relationships across the organization.
Focus on ensuring analytics tools and outputs are accurate, complete, and timely.
Proactive and strategic approach to working with internal clients.
Ability to self-organize a peer group to gain feedback.

Nice To Haves

Experience with light work in dbt or Airflow.
Experience in fintech, banking, or finance.
Experience with Looker is preferred.
Regular use of AI to assist with work, with an understanding of its trade-offs and when to rely on independent judgment.

Responsibilities

Partner semi-embedded with operations and customer support management to own complex analytical work end-to-end, from framing questions and defining measurement to delivering evidence-based narratives that influence roadmap decisions.
Build relationships with operations leadership and cross-functional partners, communicate tradeoffs, manage expectations through ambiguity, and time analytics engagement effectively.
Lead high-impact ad hoc analyses that identify opportunities or trends in operations data, and follow insights through to recommendations that affect customer outcomes.
Create self-service analytics resources, including dashboards, metric definitions, reusable queries or notebooks, and documentation.
Find creative ways to apply analytics methods and tools in the operations space, and guide stakeholders in using them to support decisions.
Mentor and support teammates through reviews, feedback, and collaboration; balance rigor with speed and escalate when scope or risk requires broader alignment.
Manage commitments for initiatives through clear communication, scope clarification, documentation of methods and limitations, impact communication, and reprioritization as needed.