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Senior Analytics Engineer

Rocket Money LogoRocket Money
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Salary

Salary range of $150,000 - $170,000 + bonus + benefits.

Location

San Francisco, CA, Washington, D.C., New York City, N.Y., or Remote (USA)

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:

  • Own the end-to-end process of designing, building, and maintaining data models that drive business insights and decision-making. You’ll work closely with stakeholders to ensure data is transformed into meaningful and actionable information.
  • Define best practices for and efficiently source new data from a variety of sources, both internal and external.
  • Work within the organization to prioritize automation over manual solutions.
  • Enhance our analytics capabilities by continuously improving data models for maintainability, performance and scalability, while ensuring they remain aligned with business goals.
  • 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.
  • 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 6+ 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 4+ 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 2+ years of experience working in a data engineering or software engineering capacity where you had to create/maintain custom data pipelines.
  • You have a passion for automating things to take people out of the loop, whether that be via prior data engineering or software engineering experience.
  • 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.
  • You have experience automating all the things with Python.
  • Experience in our specific technology stack:
    • Analytics: BigQuery/GCP, Fivetran, Looker, Mode, DBT
    • Data Engineering: Terraform, AWS

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