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.

WHAT WE DO

Our Data and Analytics consultants work with clients at all levels of the organization, from the C-suite to the shop floor, helping them to deliver on their most strategic initiatives. We’re known for making realistic, data-driven decisions that deliver value in tangible ways to our clients. Our clients ask for us on projects that require a superior combination of technical and business capabilities, people and management skills, and a collaborative mindset. We excel in understanding complex programs and strategic initiatives and breaking them into actionable pieces.

We are actively looking for professionals in the following areas:

• Data Strategy
• Data Governance
• Data Modernization
• Advanced Analytics
• Data Visualization

The ideal candidate’s experience may include but is not limited to the following:

• Have experience understanding and solving real business problems
• Have experience with presenting business case and strategy to the C-Suite
• Bring industry domain knowledge for custom data and analytics strategies
• Experience in designing and implementing data driven products and services
• Experience in designing and building high performance collaborative business and technology teams that deliver high value data solutions, data products and data analytics

Ideal candidates may call themselves Data Architects, Data Engineers, Data Scientists, Analysts and Data Governance professionals. Experience may include but not limited to the following:  

Data Strategy and Governance

• Intimately familiar with data technologies, data architecture frameworks, cloud platforms and the emerging trends in technological advancements.
• Proven experience in transforming our clients from on-prem data platforms to the cloud.
• Lead data modernization initiatives that include platform, technology and tools implementation and adoption.
• Must have experience in architecting and implementing data architecture, data engineering, reporting and analytical solutions across multiple business functions and domains.
• Conduct data management maturity assessments and identify pain points for including data quality, governance, architecture, analytics, metadata management, master data management.
• Demonstrate a rigorous and analytical problem-solving approach, leading information-gathering sessions and preparing and delivering client presentations and work products/prototypes.
• Identify data governance gaps and assess data governance maturity in a complex data environment. Should also be able to Identify the implications for data governance that arise from the technology, current processes, and skill levels in a complex data environment.

Data Architecture and Engineering

• Extensive experience or knowledge of cloud-based data platform technologies such as AWS, Microsoft Azure or Google Cloud Computing.
• Experience designing and building data platforms that support data lakes, data stores, data ingestion and transformations and API services for consuming data
• Ability to design and build complex data pipelines that either stream data in
• Experience and knowledge of programming and scripting languages, such as but not limited to Python, Node.JS and SQL
• Experience and knowledge of data integration tools and platforms
• Experience and knowledge of relational and dimensional database structures, theories, principles, and practice used in data warehousing and analytics solutions
• Ability to design and build data models using the appropriate technics to meet business objectives
• In depth knowledge of modern data technologies including Snowflake, RedShift, Azure SQL/Synaspe, Databricks or similar technologies.

Advanced Analytics and Data Visualizations

• Extensive experience or knowledge of data visualization technologies such as Tableau, Power BI, Qlik and Spotfire
• Experience with statistical and mathematical modeling, artificial intelligence and machine learning software and methods
• Experience and knowledge of programming and scripting languages such as, but not limited to, SQL, Python and R
• Experience with data modeling, data prep and machine learning tools like Alteryx, RapidMinder, RStudio and Tableau Prep
• Experience and knowledge of relational and dimensional database structures, theories, principles, and practice used in data warehousing and analytics solutions
• Experience deploying enterprise-wide reporting solutions while leveraging data visualization best practices

A career at SEI extends well beyond providing great service and thought leadership to our clients. Everyone takes an active role in building and managing our business, in an environment that runs counter to traditional consulting firms. Our consultants have a “seat at the table” and contribute to growing our business in ways that align to their interests such as growing business development opportunities, conducting interviews to support our hiring process, managing internal initiatives that build our brand or organizing trainings to share what you know with your colleagues. There is no telling what an SEI Consultant will be asked to do on a day-to-day basis – we do what it takes to get the job done.

QUALIFICATIONS

Required-

• Alignment to our core values: Excellence, Participation, Integrity and Collaboration
• Hungry, Humble, Smart
• Demonstrated business and technology acumen
• Strong written and verbal communication skills
• Understanding and experience solving real business problems
• Proven track record of delivering results
• Experience working with and/or leading a team
• Ability to work across industries, roles, functions & technologies
• Authorization for permanent employment in the United States (this position is not eligible for immigration sponsorship)

Preferred-

• Bachelor’s degree
• 8+ years professional experience
• Experience across our service offerings