Remote Jobs

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Posted
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Analytics Engineer

Rocket Money

Salary Range

110k - 150k USD / YEAR

Job Summary

At Rocket Money, we empower people to live their best financial lives. As an Analytics Engineer, you will work within interdisciplinary teams to help deliver product features and enable product analytics through accurate data modeling. You'll collaborate with engineering teams to understand how data is generated and ensure changes in the product are reflected in data models. You'll build data models for end consumers like analysts and accountants, using tools such as BigQuery/Google Cloud Platform, Fivetran, Looker, Mode, and DBT. The role requires experience with SQL templating engines, CI/CD pipelines, and BI tools. We offer competitive pay, health benefits, unlimited PTO, and other perks.

Skills

Data WarehousingSQLdbtBI tools

ABOUT ROCKET MONEY 🔮

Rocket Money’s mission is to empower people to live their best financial lives. Rocket Money offers members a unique understanding of their finances and a suite of valuable services that save them time and money – ultimately giving them a leg up on their financial journey.

ABOUT THE TEAM 🤝

Analytics Engineers at Rocket Money further our mission by helping our company understand our users and products through the lens of data. We build data models that uncover how our customers interact 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:

  • 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.

  • Confidently juggle multiple projects and priorities in our fast paced environment and work with stakeholders and analytics engineering teammates to ensure deadlines and commitments are met.

  • Work with your analytics engineering teammates to continuously iterate and improve upon our processes, best practices and technical implementation of models.

  • Build data models with the end consumer in mind, whether it be an analyst or an accountant. Own the creation of data models from source data to working with Data Analysts to properly expose the finished data models in our semantic layer (Looker).

  • Work with our data engineering and infrastructure team to define good practices for and efficiently source new data from a variety of sources, both internal and external.

  • Expertly communicate with multiple stakeholders on updates to requirements, deadlines and status of work.

  • Become an expert in multiple areas of our business and understand the logic well enough to maintain and enhance our current testing suite.

ABOUT YOU 🦄

  • You have 4+ years of working in the analytics stack within a fast paced environment and are familiar with the growing set of analytics tooling solutions. You are very comfortable working in SQL.

  • You have 3+ years of production experience with SQL templating engines, like DBT, (particularly CI/CD) and data warehouses, third party ingestion providers and BI tools.

  • You have experience exposing data models to end consumers in BI Tools.

  • 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 and test driven development. 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 strong data engineering or software engineering skills but prefer the challenge of serving analytics users via value add data modeling.

  • Experience in our specific technology stack: BigQuery/GCP, Fivetran, Looker, Mode, DBT

WE OFFER 💫

  • Health, Dental & Vision Plans

  • Competitive Pay

  • 401k Matching

  • Unlimited PTO

  • Lunch daily (in-office only)

  • Snacks & Coffee (in-office only)

  • Commuter benefits (in-office only)

Additional information: Salary range of $110,000 - $150,000 + bonus + benefits. Base pay offered may vary depending on job-related knowledge, skills, and experience.

Rocket Money, Inc. is an Affirmative Action and Equal Opportunity Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, or protected veteran status and will not be discriminated against on the basis of disability.

Pursuant to the San Francisco Fair Chance Ordinance, we will consider for employment qualified applicants with arrest and conviction records.