Senior Analytics Engineer

Salary

Salary range of $130,000 - $170,000 + bonus + benefits. Base pay offered may vary depending on job-related knowledge, skills, and experience.

About the Team

Analytics Engineers at Rocket Money further our mission by helping our company understand our users and products. We build data models that allow the entirety of the company to uncover how our customers are interacting with our products, generate cashflows, and traverse our user experiences. We work with our product and engineering teams to understand the data our applications generate, model it in useful, understandable ways, and make that data available for efficient insight generation. We have a strong preference for team players that are comfortable collaborating across teams, know how to generate understanding from data, and can deliver solutions in conjunction with product and engineering teams.

About the Role

In this role, you will:

Be the owner of data models that enable financial reporting, company-wide self-service analytics, and interfaces with company partners.
Work within interdisciplinary teams to help deliver product features, enable product analytics and experimentation through accurate and timely data modeling of customer data, and enable efficient product operations.
Deeply understand how data is generated through effective work with engineering teams. Make sure that the changes we make in our product are properly reflected in data models.
Continuously iterate and improve upon Rocket Money’s analytics and data engineer infrastructure. Create and execute plans to improve the way our team works.
Consistently and accurately expose data models to end users in self-service analytics tools like Looker in conjunction with data analysts and data scientists. Enable efficient operation of all analytics tools.
Aid the development of operational data science models by working with data scientists to engineer efficient and accurate feature engineering and model training pipelines.
With our data engineering and infrastructure team, define good practices for and efficiently source new data from a variety of sources, both internal and external.
Help partners outside of Rocket Money source and understand our data to enable profitable relationships.

About You

You have 6+ years of working in the analytics stack within a fast paced environment and are familiar with the growing set of analytics tooling solutions.
Expert grasp of common SQL dialects.
You have 3+ years of production experience with dbt (particularly CI/CD) or some other SQL templating language used to manage production analytics data models.
Familiarity with other tools in our data stack, particularly BigQuery and Looker, are highly desired.
You are obsessively detail oriented and organized.
You have an irresistible urge to understand the complexities of the data you’re working with. You love the puzzle of jumping into a messy data problem and peeling back the layers until you’ve figured out how everything works.
It’s second nature for you to break down a complex problem into specific tasks and create a plan for how to tackle those tasks. You feel comfortable taking the initiative to get started on a project and are not afraid of asking for help if you hit a road block
You have extensive experience with automated testing. You see automated testing and documentation as one of the keys to scaling.
You are a strong written communicator. You are used to working in tickets and sprints.
You have experience partnering with analytics teams, business stakeholders, and engineers to deliver analytics solutions to business problems. You are confident in your ability to speak with both technical and non-technical teams
You find it enjoyable working with engineers to define data models that enable both efficient operation of applications and capture the data necessary to enable analytics and data science use cases.

Bonus points if:

You have experience working with accounting or financial data, including working with data that powers enterprise accounting systems.
You have strong data engineering skills but prefer the challenge of serving analytics users via value add data modeling.

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