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 the Role:

We're looking for a Senior Sales Compensation Analyst to join our Revenue Operations team. As a senior individual contributor, you will serve as a hands-on operator, subject matter expert, and strategic partner to our sales organization — owning end-to-end compensation administration while independently shaping the compensation programs and operational frameworks that drive Gusto's growth.

This is a high-visibility role at the intersection of Sales, Finance, and Revenue Operations. You'll bring deep expertise in sales compensation administration, advanced analytical capabilities, and a track record of building scalable programs that are fair, accurate, and motivating. You'll operate with a high degree of autonomy alongside the Head of Sales Compensation — driving plan administration, contributing to plan design for assigned segments, and setting the operational and analytical standard for the team. You'll leverage AI tools to push the boundaries of what our team can deliver.

About the Team:

The Sales Compensation team at Gusto sits within the Revenue Operations organization and serves as the backbone of how Gusto's sales force is motivated, rewarded, and aligned to company growth. We are a small, high-impact team with outsized visibility — our work touches every quota-carrying role across the company and directly influences how Gusto attracts, retains, and drives performance from top sales talent.

Here’s what you’ll do day-to-day:

• Own sales compensation administration for assigned teams — execute accurate, on-time commission calculations, payment processing, crediting, draws, clawbacks, and dispute resolution each pay cycle; Serve as the team's Xactly platform owner and subject matter expert, defining configuration standards, driving platform decisions, and maintaining data integrity across plan setup, participant management, and workflow automation 
• Own monthly reporting & analytics for assigned segments — deliver attainment summaries and payout forecasts to Sales, Finance/Accounting, and Rev Ops; maintain KPI dashboards and perform ad hoc analysis on performance trends and budget adherence.
• Contribute to plan design for assigned segments — Support and, where designated, independently own compensation plan inputs for assigned sales segments, including rate validation, accelerator analysis, and rules of engagement; build financial models and scenario analyses that inform quota-setting and plan design decisions; connect compensation mechanics to broader outcomes across Finance, HR, and Sales Strategy
• Define and improve processes and compliance — document and continuously improve comp processes; maintain adherence to internal compliance standards and accounting rules; ensure role changes, new hires, and terminations are reflected accurately across Xactly and downstream systems
• Lead assigned cross-functional initiatives - Drive projects spanning Sales, Finance, HR, and Rev Ops; use data and structured analysis to influence stakeholders and build alignment across functions
• Leverage AI to elevate comp operations — actively incorporate AI tools to automate repetitive tasks, accelerate reporting, and surface insights; partner with the Head of Sales Compensation to identify and scale AI-driven improvements across the team 

Here’s what we're looking for:

• 8+ years of hands-on sales compensation administration experience with demonstrated end-to-end ownership of commission processes in a high-growth environment 
• Experience in full-cycle comp administration — calculations, crediting, draws, clawbacks, and dispute resolution. 
• Xactly platform expertise - intermediate-to-advanced admin required (certification preferred); proven ability to own system configuration, data integrity, and workflow design; Salesforce and Tableau/Looker/Power BI proficiency; other ICM platforms a plus
• Advanced analytical skills - compensation modeling, scenario analysis, and reporting; solid understanding of quota-setting methodologies, GTM motions, and sales roles (AE, AM, SDR, overlay) 
• Cross-functional influence — track record of leading initiatives and driving alignment across Sales, Finance, HR, and Operations without direct authority  
• AI competency — actively uses AI tools to automate tasks, accelerate analysis, and improve accuracy with a habit of exploring and applying new tools practically 
• Attributes — detail-oriented, proactive, and highly organized; clear communicator who can simplify complex comp mechanics for reps, managers, and cross-functional partners
• Bachelor's degree in Finance, Business, Mathematics, or related field — or equivalent experience

Our cash compensation amount for this role is $113,880 to $139,500 for Denver, Atlanta & Las Vegas. $138,365 to $169,500 for San Francisco & New York. $106,940 to $131,000 for Phoenix. Final offer amounts are determined by multiple factors including candidate location, experience and expertise and may vary from the amounts listed above.

BASE SALARY: $150,000 to $190,000 per year, paid semi-monthly

MUST HAVE:

• 5+ years of experience in data engineering within fast-paced, cloud-native environments
• Deep expertise in Python, SQL, Docker, and AWS (S3, Glue, Kinesis, Athena/Presto)
• Experience building and managing scalable ETL pipelines and data lake infrastructure
• Familiarity with distributed systems, Spark, and data quality best practices
• Strong cross-functional collaboration skills to support BI, analytics, and engineering teams

EXPERIENCE: 5+ years of data engineering experience in an AWS-based environment where data powers decision-making across product, marketing, and operations.

YOUR ROLE

Lead scalable data engineering efforts that empower cross-functional teams with reliable, timely, and actionable data, ensuring Launch Potato’s analytics and business intelligence infrastructure fuels strategic growth.

OUTCOMES

• Build and optimize scalable, efficient ETL and data lake processes that proactively catch issues before they impact the business
• Own the ingestion, modeling, and transformation of structured and unstructured data to support reporting and analysis across all business units
• Partner closely with BI and Analytics to deliver clean, query-ready datasets that improve user acquisition, engagement, and revenue growth
• Maintain and enhance database monitoring, anomaly detection, and quality assurance workflows
• Serve as the internal point of contact for reporting infrastructure—delivering ad hoc data analyses and driving consistent data integrity
• Drive adoption and advancement of Looker dashboards by ensuring robust and scalable backend data support
• Contribute to the future of Launch Potato’s data team by mentoring peers and shaping a high-performance, quality-first engineering culture

COMPETENCIES

• Data Engineering Mastery: Demonstrates technical excellence in building data pipelines, troubleshooting distributed systems, and scaling infrastructure using AWS and open-source tools
• Cross-Functional Collaboration: Communicates clearly across technical and non-technical teams, translating business needs into robust data solutions
• Proactive Ownership: Operates with a strong sense of accountability; identifies and solves data issues independently and efficiently
• Quality-Driven Execution: Holds a high bar for data accuracy, auditability, and documentation throughout all systems and workflows
• Strategic Thinking: Anticipates how data infrastructure impacts wider company OKRs and proactively suggests improvements and innovations
• Growth Mindset: Seeks out opportunities to elevate team capabilities, mentor others, and stay ahead of evolving best practices in data engineering

TOTAL COMPENSATION

Base salary is set according to market rates for the nearest major metro and varies based on Launch Potato’s Levels Framework. Your compensation package includes a base salary, profit-sharing bonus, and competitive benefits. Launch Potato is a performance-driven company, which means once you are hired, future increases will be based on company and personal performance, not annual cost of living adjustments.

BASE SALARY: $150,000 to $190,000 per year, paid semi-monthly

MUST HAVE:

• 5+ years of experience in data engineering within fast-paced, cloud-native environments
• Deep expertise in Python, SQL, Docker, and AWS (S3, Glue, Kinesis, Athena/Presto)
• Experience building and managing scalable ETL pipelines and data lake infrastructure
• Familiarity with distributed systems, Spark, and data quality best practices
• Strong cross-functional collaboration skills to support BI, analytics, and engineering teams

EXPERIENCE: 5+ years of data engineering experience in an AWS-based environment where data powers decision-making across product, marketing, and operations.

YOUR ROLE

Lead scalable data engineering efforts that empower cross-functional teams with reliable, timely, and actionable data, ensuring Launch Potato’s analytics and business intelligence infrastructure fuels strategic growth.

OUTCOMES

• Build and optimize scalable, efficient ETL and data lake processes that proactively catch issues before they impact the business
• Own the ingestion, modeling, and transformation of structured and unstructured data to support reporting and analysis across all business units
• Partner closely with BI and Analytics to deliver clean, query-ready datasets that improve user acquisition, engagement, and revenue growth
• Maintain and enhance database monitoring, anomaly detection, and quality assurance workflows
• Serve as the internal point of contact for reporting infrastructure—delivering ad hoc data analyses and driving consistent data integrity
• Drive adoption and advancement of Looker dashboards by ensuring robust and scalable backend data support
• Contribute to the future of Launch Potato’s data team by mentoring peers and shaping a high-performance, quality-first engineering culture

COMPETENCIES

• Data Engineering Mastery: Demonstrates technical excellence in building data pipelines, troubleshooting distributed systems, and scaling infrastructure using AWS and open-source tools
• Cross-Functional Collaboration: Communicates clearly across technical and non-technical teams, translating business needs into robust data solutions
• Proactive Ownership: Operates with a strong sense of accountability; identifies and solves data issues independently and efficiently
• Quality-Driven Execution: Holds a high bar for data accuracy, auditability, and documentation throughout all systems and workflows
• Strategic Thinking: Anticipates how data infrastructure impacts wider company OKRs and proactively suggests improvements and innovations
• Growth Mindset: Seeks out opportunities to elevate team capabilities, mentor others, and stay ahead of evolving best practices in data engineering

TOTAL COMPENSATION

Base salary is set according to market rates for the nearest major metro and varies based on Launch Potato’s Levels Framework. Your compensation package includes a base salary, profit-sharing bonus, and competitive benefits. Launch Potato is a performance-driven company, which means once you are hired, future increases will be based on company and personal performance, not annual cost of living adjustments.

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 the Role

You own our marketing technology stack — lifecycle infrastructure that powers email and SMS programs, and tracking systems that keep paid media attribution honest.

You'll design and maintain the systems that let a lean, AI-powered marketing team move fast and measure accurately. That means Iterable journeys and CDP audiences that run lifecycle programs on autopilot, a conversion tracking layer that stays clean across every ad platform, and automation that eliminates manual work from campaign launches to performance monitoring. You'll also drive cross-functional initiatives with Engineering, Product, and Growth Science to get critical tracking and infrastructure work prioritized. Senior IC role, no direct reports.

What You'll Do

1. Lifecycle Platform & Campaign Infrastructure

• Own Iterable end-to-end: configuration, journey architecture, lifecycle triggers, and audience management for welcome, nurture, and re-engagement programs.
• Manage our CDP (Segment Personas): define audience segments, maintain governance and naming conventions, and work with Engineering to ensure data flows to Iterable cleanly.
• Build AI-powered email and SMS template systems — modular, dynamic, and populated by AI at scale — so our lifecycle team can ship programs without relying on agencies or one-off builds.
• Train the team on platform capabilities and self-serve campaign creation so the lifecycle lead can focus on strategy, not production.

2. Conversion Tracking & Attribution

• Own Google Tag Manager and our Segment event taxonomy. Partner with Engineering on event tracking implementation, maintain event taxonomy documentation, and troubleshoot conversion data gaps across ad platforms.
• Partner with Engineering to implement and verify CAPI, enhanced conversions, and server-side tracking setups. You drive requirements, validate implementation, and own ongoing QA — Engineering builds it.
• Escalate and drive Engineering/Product prioritization when tracking infrastructure needs investment.

3. Automation, Tooling & Experimentation

• Build automated budget pacing alerts, performance anomaly detection, and campaign QA workflows (broken links, UTM validation, tracking checks) for both paid and lifecycle programs.
• Use Claude, Python, Gumloop and AI tools to build self-serve workflows that eliminate manual operational work across the team. Train team members on AI tools for content generation, analysis, and self-serve campaign creation.
• Partner with Growth Science on budget allocation analysis, channel decisions, measurement planning, and incrementality testing.

What You'll Need

Technical Skills:

• Expert in Iterable, Braze, or comparable ESP at enterprise scale (millions of sends)
• Strong HTML/CSS for responsive email templates; comfortable reading JavaScript
• Experienced with CDP platforms (Segment Personas or similar)
• Working knowledge of GTM, CAPI, enhanced conversions, and server-side tracking
• Proficient with Python scripting and no-code automation tools (Gumloop, Make, Zapier)
• Expert with AI tools (Claude, Cursor) for generating code, templates, and analysis
• Proficient in SQL for campaign analysis and troubleshooting

Experience:

• 5–7+ years in marketing operations, with primary depth in lifecycle/email platform ownership at scale
• Track record building infrastructure — not running campaigns — that measurably increases team velocity
• Proven ability to drive data infrastructure through Engineering and Product without direct authority
• Comfortable spanning acquisition and lifecycle — you understand how performance marketing and lifecycle programs interact

Mindset:

• Infrastructure builder: you design systems that eliminate entire categories of manual work
• AI-native: you use AI tools daily — for coding, content, analysis, and problem-solving
• High-agency IC: you architect solutions, prototype independently, and build them yourself

Bonus Points

• High-consideration, high-value transactional businesses (real estate, automotive, financial services)
• Amplitude or Optimizely experimentation platform experience
• Figma for prototyping templates
• Analytics engineering or data visualization (Looker, Mode, Tableau)
• Segment CDP, mobile push, or in-app messaging experience

Compensation

The base pay range for this position is $172,000–$238,000 Canadian Dollars annually, plus RSUs and bonuses. Pay within this range varies by work location and may also depend on your qualifications, job-related knowledge, skills, and experience. We also offer a comprehensive package of benefits including unlimited PTO, medical/dental/vision insurance, life insurance, and 401(k) to eligible employees.

About the Role

You own our marketing technology stack — lifecycle infrastructure that powers email and SMS programs, and tracking systems that keep paid media attribution honest.

You'll design and maintain the systems that let a lean, AI-powered marketing team move fast and measure accurately. That means Iterable journeys and CDP audiences that run lifecycle programs on autopilot, a conversion tracking layer that stays clean across every ad platform, and automation that eliminates manual work from campaign launches to performance monitoring. You'll also drive cross-functional initiatives with Engineering, Product, and Growth Science to get critical tracking and infrastructure work prioritized. Senior IC role, no direct reports.

What You'll Do

1. Lifecycle Platform & Campaign Infrastructure

• Own Iterable end-to-end: configuration, journey architecture, lifecycle triggers, and audience management for welcome, nurture, and re-engagement programs.
• Manage our CDP (Segment Personas): define audience segments, maintain governance and naming conventions, and work with Engineering to ensure data flows to Iterable cleanly.
• Build AI-powered email and SMS template systems — modular, dynamic, and populated by AI at scale — so our lifecycle team can ship programs without relying on agencies or one-off builds.
• Train the team on platform capabilities and self-serve campaign creation so the lifecycle lead can focus on strategy, not production.

2. Conversion Tracking & Attribution

• Own Google Tag Manager and our Segment event taxonomy. Partner with Engineering on event tracking implementation, maintain event taxonomy documentation, and troubleshoot conversion data gaps across ad platforms.
• Partner with Engineering to implement and verify CAPI, enhanced conversions, and server-side tracking setups. You drive requirements, validate implementation, and own ongoing QA — Engineering builds it.
• Escalate and drive Engineering/Product prioritization when tracking infrastructure needs investment.

3. Automation, Tooling & Experimentation

• Build automated budget pacing alerts, performance anomaly detection, and campaign QA workflows (broken links, UTM validation, tracking checks) for both paid and lifecycle programs.
• Use Claude, Python, Gumloop and AI tools to build self-serve workflows that eliminate manual operational work across the team. Train team members on AI tools for content generation, analysis, and self-serve campaign creation.
• Partner with Growth Science on budget allocation analysis, channel decisions, measurement planning, and incrementality testing.

What You'll Need

Technical Skills:

• Expert in Iterable, Braze, or comparable ESP at enterprise scale (millions of sends)
• Strong HTML/CSS for responsive email templates; comfortable reading JavaScript
• Experienced with CDP platforms (Segment Personas or similar)
• Working knowledge of GTM, CAPI, enhanced conversions, and server-side tracking
• Proficient with Python scripting and no-code automation tools (Gumloop, Make, Zapier)
• Expert with AI tools (Claude, Cursor) for generating code, templates, and analysis
• Proficient in SQL for campaign analysis and troubleshooting

Experience:

• 5–7+ years in marketing operations, with primary depth in lifecycle/email platform ownership at scale
• Track record building infrastructure — not running campaigns — that measurably increases team velocity
• Proven ability to drive data infrastructure through Engineering and Product without direct authority
• Comfortable spanning acquisition and lifecycle — you understand how performance marketing and lifecycle programs interact

Mindset:

• Infrastructure builder: you design systems that eliminate entire categories of manual work
• AI-native: you use AI tools daily — for coding, content, analysis, and problem-solving
• High-agency IC: you architect solutions, prototype independently, and build them yourself

Bonus Points

• High-consideration, high-value transactional businesses (real estate, automotive, financial services)
• Amplitude or Optimizely experimentation platform experience
• Figma for prototyping templates
• Analytics engineering or data visualization (Looker, Mode, Tableau)
• Segment CDP, mobile push, or in-app messaging experience

Compensation

Our compensation plan consists of a base salary, Opendoor equity and a comprehensive package of benefits including paid time off, paid holidays, medical/dental/vision insurance, basic life insurance, and 401(k) to eligible employees.  All compensation parameters are based on experience.

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.