About the Role

The Challenge

Do you know what it takes to evolve "some dbt models" into a fully governed, well-tagged data platform that every function in the company trusts? Are you ready to take IaC from 60% to 100% coverage while building multi-region resiliency for sensitive financial data?

The Team and Scope

As our Data and Platform Engineering Manager, you'll lead a team of six engineers — three data and three platform — reporting directly to the CTO. You'll steward the full lifecycle from raw ingestion to governed data assets, while growing Caribou's GCP infrastructure toward complete automation and cost efficiency. This role sits at the heart of Caribou's engineering leadership team — a meaningful seat at the table as we scale toward our next stage.

Our Stack and Philosophy

We're on GCP (GKE, Cloud Storage, CloudSQL, BigQuery, Cloud Composer) and use dbt and Pulumi. We care more about your engineering fundamentals and curiosity than your specific history with these tools. If you're experienced in AWS, Snowflake, or Terraform and excited to apply those principles to our stack, we want to talk to you.

Your First 90 Days

Your primary mission will be to lead your data engineers, alongside our analytics and data science teams, in maturing our medallion and marts architecture. We aim to deliver material protection against data evolution for the organization by the second half of 2026.

What You Will Do

• Shape the architectural vision for our data platform, ensuring high-quality, self-service data assets across all business functions
• Lead the SDLC for your team, delivering platform and infrastructure improvements consistently and with clear communication
• Strengthen Caribou's GCP infrastructure by growing IaC coverage, optimizing cloud spend, and building platform resiliency
• Collaborate with Analytics and Product to understand platform needs and translate that context into a prioritized roadmap
• Mentor and coach engineers to deepen their expertise across data modeling, platform engineering, and technical leadership
• Help shape Caribou's engineering culture, contributing a perspective that touches every part of the business

Candidates are welcome to work remotely from the states of AZ, CO, DC, IL, MD, TX, and VA with a preference for the Chicago IL, Denver CO, or Phoenix AZ areas.  Caribou does provide the option to work in-office or hybrid from our Denver, CO or Chandler, AZ offices.  We may consider remote candidates in CA, FL, MA, NY, OR, WA, and WI, subject to additional approval. Eligibility by state is subject to change.  

Please let us know if you need accommodations at any point during the interview process.

What We Look For

• Experience leading engineers who build and mature data platforms — from raw ingestion pipelines through governed assets business teams rely on
• Fluency with the modern data stack: dbt, a cloud warehouse (BigQuery or equivalent), orchestration tooling, and sound data modeling patterns
• Cloud infrastructure fluency — IaC tooling (Terraform or equivalent), cost discipline, and the operational rigor a regulated financial environment demands
• Collaborative leaders who favor context over command and control, measuring success by the growth of those around them
• Curious, life-long learners equally at home in a data modeling discussion and a deep infrastructure review, bringing the same rigor to both.

We know strong candidates rarely check every box, and backgrounds in this space take many shapes — analytics engineers who grew into platform ownership, SREs who moved into data, DevOps practitioners who found their way to EM. If this role excites you, we'd love to hear from you.

Interview Roadmap:

• Recruiter phone interview (30 mins)
• At-home coding assessment (60 mins)
• Hiring Manager video interview (60 mins)
• Final interview loop - (4) one-hour video interviews scheduled across 1-4 business days

How we will take care of you

Everyone at Caribou is a valued team member. Our compensation and benefits package includes: 

• Competitive compensation: $175k - $215k
• Eligible for annual performance based bonus
• Equity options
• 401k savings program
• Generous paid time off including: Flexible Time Off (FTO) for all employees and 100% paid parental leave for all parents.
• Robust wellness benefits including company-paid plans for health, dental, vision, mental health, disability and basic life insurance.
• Optional benefits to suit your individual circumstances such as HSAs, FSAs, supplemental life and medical insurance, and pet insurance.
• Up to $1,000 per year for eligible professional development expenses.

About the Role

The Revenue Operations team at Gusto is a full-stack team responsible for data, analytics, and operational excellence in pursuit of scaling our revenue growth. The Go-To-Market Analytics team is one functional area, responsible for defining and owning the metrics for scaling our Sales teams. 

Gusto is looking for a Revenue Analytics Engineer to build and maintain foundational data infrastructure that is crucial to growing and scaling our Sales efforts. In this role, you will partner with our GTM analysts to scope and deliver data products for an audience ranging from company and revenue leadership to operational and frontline sales. In doing so, you will own significant portions of our sales data from end-to-end, focusing on the transformation, design, and visualization workflows. In addition, you will establish best practices for systems design and workflows to maximize usefulness of AI at scale. 

This role will report to the Head of Go-To-Market analytics, and partner closely with Data Science, Data Platform, and Business Technology teams. 

Here’s what you’ll do day-to-day:

• Establish relationships with internal stakeholders to determine business needs, scoping and delivering solutions through data products
• Design, build, and maintain data pipelines and dashboards to automate “keep the lights on” work out of manually-managed processes
• Build a data foundation by incorporating business logic into raw data tables, laying the groundwork to enable value-add insights
• Create a dynamic reporting environment based on stakeholder needs
• Identify data discrepancies and set best practices for data logic to create a clean and well-documented environment
• Collaborate with broader data organization as steward to the definition and process management of core Gusto metrics

Here’s what we're looking for:

• Education or work experience in Engineering or Computer Science, or a related technical field 
• 7+ years of experience in an analytics engineering, business intelligence, or technical data analytics role
• Experience with SQL and ETL optimization techniques, especially within cloud-based data warehouses like Redshift, Snowflake, etc.
• Command-line experience and familiarity with version control collaboration tools (git)
• Experience with data pipeline management technologies with dependency checking, such as Airflow, as well as schema design and data modeling tools (dbt)
• Experience with data visualization technologies, e.g., Tableau, Looker, Sigma, Mode, Hex
• Experience with Python and data ingestion tools
• Ability to problem-solve open-ended problems and project manage dependencies and timelines to optimal outcomes
• Ability to demonstrate tools, business intuition, and attention to detail for data validation and QA 

Our cash compensation amount for this role is targeted at $138,000-156,000 in Denver & most remote locations, and $168,000-189,000 in New York & San Francisco Bay Area. Stock equity is additional. Final offer amounts are determined by multiple factors including candidate experience and expertise and may vary from the amounts listed above.

ABOUT ROCKET MONEY 🔮

Rocket Money’s mission is to meaningfully improve the financial prosperity of millions of people. 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 🤝

Data Platform Engineers at Rocket Money further our mission by building and maintaining the infrastructure that enables our company to understand our users and products through reliable, scalable data systems. We build the foundational platform that ingests, processes, and serves data—enabling our Data Analytics, Machine Learning, and Software Engineering teams to build data products efficiently. We work closely with engineering teams to ensure data is captured correctly at the source, design resilient pipelines, and create self-service capabilities that empower stakeholders.

The Data Platform team is in an exciting phase of growth and formalization. While we have established tools and processes in place (dbt, BigQuery, Terraform), we're actively building the comprehensive standards, practices, and systems that will scale with Rocket Money as it grows. We're looking for engineers who can take ownership and evolve workflows into reliable, well-documented, production-grade systems. This is an opportunity to shape architectural decisions, establish team practices, and define how Rocket Money works with data for years to come.

We have a strong preference for process-oriented systems thinkers who excel in balancing stakeholder requirements, technical debt, and organizational complexity—and who thrive in environments where they need to create structure from ambiguity. You'll need to be comfortable making principled decisions, taking ownership not just of code but of outcomes, and operating with significant autonomy as we build the platform together.

ABOUT THE ROLE 🤹

In this role, you will:

• Be an end-to-end owner of our data platform infrastructure, ensuring its security, usability, and performance. Work closely with analytics engineers, machine learning engineers, and software engineers to ensure the platform meets their needs.
• Make collaborative decisions about data tooling, pipeline design, and governance, and implement opinionated interfaces that facilitate easy and best-practice-aligned development for other teammates.
• Continuously improve failure rates for data sources by moving alerting “to the left”; i.e. catching and quarantining bugs/failures as close to the source as possible.
• Analyze patterns in how source data is generated, modeled, and consumed. Work with stakeholders to implement the best solution when new data sources are added.
• Take ownership of existing tools and workflows that may be functional but lack formal structure, documentation, or reliability measures. You'll assess what's working, identify gaps, and systematically improve systems to production-grade quality.
• Document everything you build knowing that you're creating the foundation others will build upon. Your runbooks, architecture decision records, and system documentation will become the institutional knowledge of our data platform.
• Proactively communicate with multiple stakeholders on platform capabilities, technical constraints, architectural decisions, project priorities, and platform support.
• Confidently juggle multiple projects and priorities in our fast-paced environment and work with stakeholders and platform teammates to ensure infrastructure changes, migrations, and improvements are delivered on schedule.
• Automate aggressively and deliberately; anything from GitHub Actions to Slack Workflows to minimize repetitive tasks. Effectively judge when the level of effort is appropriate and avoid over-engineering.

ABOUT YOU 🦄

• You have 6+ years of experience working with data infrastructure, data engineering, or platform engineering within a fast-paced environment. You are highly proficient with SQL, Python, and cloud-based Infrastructure-as-Code (e.g. Terraform), and comfortable working with bash/shell scripting.
• You have 4+ years of production experience with modern data stacks including data warehouses (BigQuery, Snowflake, or Redshift), orchestration tools, managed ingestion services, and infrastructure as code (Terraform, Pulumi, or CloudFormation).
• You have 2+ years of experience building and maintaining production data pipelines, whether through ELT tools, custom applications, streaming systems, or event-driven architectures.
• You've successfully "professionalized" data infrastructure before—taking scrappy, working systems and evolving them into reliable, well-documented, production-grade platforms. You can articulate what "production-ready" means in a data context.
• You have a bias toward action and aren't paralyzed by imperfect solutions. You understand when "good enough for now with a plan to improve" beats "perfect but six months late." You ship incrementally and iterate based on feedback.
• You're comfortable being the first person to tackle a problem. You don't need extensive mentorship or detailed tickets—you can take a high-level business need and figure out the technical approach. That said, you know when to ask for help and can articulate what you need.
• You take ownership seriously—not just of writing code, but of outcomes. When you build something, you implement monitoring, write runbooks, create alerts, and ensure it can be maintained by others. You think about the full lifecycle of systems, not just initial delivery.
• You have strong opinions, weakly held. You can make and defend architectural decisions, but you're open to feedback and willing to change course when presented with better information. You can disagree and commit.
• You understand that "building from scratch" doesn't mean rejecting existing tools—it means thoughtfully selecting, configuring, and integrating managed services and open-source solutions to create a cohesive platform. You know when to build and when to buy.
• You have experience making big changes to critical data infrastructure. You’ve successfully re-architected, migrated, or upgraded data tooling that has strict SLA’s, without significantly affecting downstream stakeholders.

Bonus points if:

• You have led a data infrastructure migration or modernization project where you defined the vision, approach, and implementation.
• You have created internal tools, frameworks, or CLIs that improved how teams work with data (not just one-off scripts).
• You have established data platform best practices like CI/CD workflows, testing frameworks, or observability standards where none existed.
• Expertise in cloud platforms and technologies analogous to our stack:
  • Our stack: GCP (BigQuery, Datastream, Cloud Functions, Vertex AI, GCS), dbt, Fivetran, Postgres, Python, Terraform, Looker, Retool
  • Analogous experience: AWS (Redshift, DMS, Lambda, SageMaker, S3) or Azure (Synapse, Data Factory, Functions), Snowflake, Airbyte/Stitch, infrastructure as code tools, BI platforms

WE OFFER 💫

• Health, Dental & Vision Plans
• Life Insurance
• Long/Short Term Disability
• Competitive Pay
• 401k Matching
• Team Member Stock Purchasing Program (TMSPP)
• Learning & Development Opportunities
• Tuition Reimbursement
• Unlimited PTO
• Daily Lunch, Snacks & Coffee (in-office only)
• Commuter benefits (in-office only)

Additional information: Salary range of $160,000 - $200,000 + 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.

ABOUT ROCKET MONEY🔮

Rocket Money’s mission is to meaningfully improve the financial prosperity of millions of people. 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.

Please note: We strongly encourage team members to be in the office 1-2 days per week, though there is no formal in-office requirement.

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.

Our team values:

• Collaboration - We're team players who excel at cross-functional partnership with product and engineering teams
• Impact - We transform raw data into strategic insights that drive business decisions
• Growth - We continuously refine our craft while supporting each other's professional development

We're growing our team and are looking for an Analytics Engineering Team Leader who is committed to building an equitable, healthy work environment where team members thrive. In this role, you'll elevate our Analytics Engineering practice, mentor talented engineers, be a hands on contributor to our dbt and LookML code bases, and champion data-driven decision making across the organization. You'll help shape how Rocket Money uses data to understand our customers and products while building a world-class team.

Our Tech Stack: BigQuery, dbt, Looker, Amplitude, Fivetran, Datadog, git, Deepnote

IN THIS ROLE, YOU'LL:

• Own ambitious yet achievable quarterly roadmaps that drive our business forward by building tooling that allows the team to deliver faster, more consistent work and directing cross-team analytics efforts that inform strategy.
• Lead and manage a team of 4-6 analytics engineering professionals, creating processes for autonomous operation with cross-functional teams while maintaining high quality standards and accountability and supporting individual growth.
  • Evolve team development standards, including technical skill frameworks, career ladders, and learning pathways. Create a culture of continuous improvement through code reviews, knowledge sharing sessions, and mentorship programs that elevate the entire team's capabilities.
  • Champion data quality and attention to detail as core team values, establishing review processes and quality gates that ensure the accuracy and reliability of analytics outputs while still shipping iteratively and building stakeholder trust through visible progress.
• Foster strong working relationships with other leaders at the company, advocating for your team's involvement at the right time and driving high quality analytics delivery across teams.
• Address problems with performance directly and make decisions based on what's best for our users, team members, and business. Create highly functional teams and processes that make best use of data analytics resources.
• Be accountable for making, measuring, and delivering on team commitments, as well as pivoting when necessary to keep the team focused on the most impactful work.
• You're energized by problems that don't come with clearly defined requirements, and you know how to work with stakeholders to scope what's actually measurable.

ABOUT YOU 🦄

Technical Leadership

• You have hands-on experience with the modern analytics stack (e.g., dbt, Snowflake/BigQuery, Looker/Tableau/Databricks/Omni) and can guide technical decisions while establishing quality standards and review processes that ensure data accuracy.
• You have deep expertise in analytics engineering and a strong understanding of data systems and processes, especially delivery of maintainable/scalable models that meet stakeholder needs and support self service. You have experience implementing analytics engineering best practices (version control, testing, documentation, CI/CD) and can balance delivery speed with analytical rigor.
• You have strong software engineering fundamentals and the curiosity to dive into application codebases to understand data generation at its source. You believe analytics engineers should understand the full data lifecycle - from how events are instrumented in production code to how they're modeled in the warehouse.

Strategic & Business Acumen

• You can translate business objectives into technical roadmaps and have experience building self-service analytics strategies that scale across organizations.
• You lead a team that gets ahead of the business, building tooling and documentation so stakeholders can answer their own questions without waiting on a ticket.

People Leadership

• You have 5+ years of experience managing analytics engineering professionals. You've successfully led a team of embedded professionals and know how to cultivate a culture of autonomy within cross-functional teams.
• You can tailor your management style to suit your employees, identifying where some people might succeed with a more hands-off approach than others. You're passionate about developing talent and have a track record of building career frameworks, implementing mentorship programs, and helping analytics engineers grow from mid-level to senior roles.

Communication & Collaboration

• You excel at stakeholder management and can build effective relationships across the organization. You self-organize a peer group to gain feedback.
• You're an exceptional communicator who can explain complex data concepts to non-technical stakeholders and advocate for data-driven decision making at the executive level.

Growth Mindset

• You want to continue to grow and learn. You are excited by hard problems and big challenges.
• Experience in fintech, banking, or finance is a plus.

WE OFFER 💫

• Health, Dental & Vision Plans
• Life Insurance
• Long/Short Term Disability
• Competitive Pay
• 401k Matching
• Team Member Stock Purchasing Program (TMSPP)
• Learning & Development Opportunities
• Tuition Reimbursement
• Unlimited PTO
• Daily Lunch, Snacks & Coffee (in-office only)
• Commuter benefits (in-office only)

Additional information: Salary range of $170,000 - $220,000/year + bonus + benefits. Base pay offered may vary depending on job-related knowledge, skills, and experience.

Rocket Money 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.