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.

Location

This role requires working from our downtown Toronto office 4 days/week (Mon, Tues, Thurs, Fri). Candidates must be based within a 50-mile commuting distance of the office.

About the Role

At Opendoor, AI isn’t a side project - it’s how we work. Across the company, teams default to AI to solve problems, ship faster, and remove friction from everything we do. You will help define the future of how we work by building AI powered workflows, automation, and experiences that drive leverage across Finance — spanning month-end close, SEC Reporting, FP&A, Technical Accounting, Tax, Procurement, Accounts Payable, and Payroll. This is high agency work in high ambiguity - turning messy problems into clean solutions, prototyping fast, and shipping.

You'll make systems design and tooling decisions that affect how our Finance operations scale – so we need people who think critically about what and why they build, the impact it will have on our team, and how to measure success. 

We're looking for AI-native builders who know how to automate complex operational workflows. The accounting and finance domain knowledge can be learned — what matters most is that you're wired to build, that you default to AI in how you approach problems, and that you can map messy business processes into clean, automated systems. 

Why Join Us

• Build AI automation for our Financial Operations from the ground up
• Work on cutting-edge systems directly impacting key Finance processes in a public company 
• Collaborate with talented engineers and finance team members
• Access to enterprise AI tools — Claude Code, Cursor, and LLM APIs. We invest heavily in AI infrastructure so you can build and experiment.

What You'll Do

This is a hands-on individual contributor role. You will design, build, and ship automations — not just evaluate tools or write strategy decks.

• Turn complex Accounting and Finance problems into clear system designs, experiments, and implementation plans
• Build and maintain AI-powered automation that improves operational efficiency, accuracy, and scale across Finance functions
• Automate workflows (journal entries, reconciliations, flux analysis) using SQL, Python, and agentic AI
• Maintain clean, auditable data throughout automated workflows, with dashboards and controls that support both operational and compliance needs
• Partner with the internal SOX team and external auditors to ensure automated processes meet compliance standards and are well-documented
• Build and scale AI literacy across the Finance team through runbooks, documentation, best practices, and hands-on training 

What You'll Bring

• At least 5+ years of work experience building automation, operational workflows, or data systems in any industry. 
• Familiarity with LLM deployment, context engineering and comfortable writing SQL or Python code
• Understanding of machine learning lifecycle concepts: training, evaluation, deployment, monitoring

Systems Thinking: You understand how data flows through operational systems. You can look at a business process, identify the inputs, outputs, dependencies, and failure modes, and design automation around it.

System Design: You take complex, messy problems and reduce them to simple, durable architecture. 

Communication: Articulate problems clearly to both technical and non-technical audiences. You write clean documentation, build dashboards that tell a story, and can walk a stakeholder through your design rationale.

AI Alchemy: You have high agency and a tinkering mindset. You default to experimenting, running variations with new tools and methods - LLMs, automation platforms, coding assistants until you can transmute data into high quality results. You're comfortable writing SQL code, working with APIs, and stitching tools together to ship solutions fast.

Impact Driven: You optimize for impact over novelty, choosing the right tools for the job and ensure performance, scalability and resiliency.

Bonus if you have:

• Experience in Accounting or Finance 
• Comfort working in regulated or compliance-sensitive environments

Tools and Technologies

You'll work across a range of tools and we expect this list to evolve. Ideal candidates will have experience with the following tech stack:

• AI coding assistants: Claude Code, Cursor, or similar 
• Workflow automation: Gumloop or similar platforms
• MCP integrations
• Agentic AI frameworks or building automation flows 
• Data / ERP platforms: Snowflake, NetSuite, Ramp or similar 

Note: Opendoor provides enterprise-level access to all AI tools listed above. Our engineers currently consume billions of AI tokens per month across the company and are not constrained by token limits or personal account restrictions.

Compensation

Our compensation plan consists of a base salary and Opendoor equity  in addition to 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.

 #LI-DM

#LI-Onsite

Your Impact

Axon Enterprise (Nasdaq: AXON) is seeking a Data Science Principal within the Office of the Chief Accounting Officer (CAO). This is a hands-on enabler role for a technically exceptional professional with deep finance and accounting domain expertise. Your primary mission is to ensure that Axon’s AI builders, process owners, decision-makers, and auditors can operate with clean, trusted, well-governed, and audit-ready data. You will spend roughly half your time building data analytics tools and pipelines—leveraging AI as a development accelerator—to support complex, large-scale projects including mergers and acquisitions (M&A) integration, enterprise resource planning (ERP) system deployments, upstream data remediation, and SOX compliance initiatives.

The other half is strategic: partnering across Controllership, Finance Operations, Financial Planning and Analysis (FP&A), Internal Audit, and Technology to establish the data foundation that makes AI, automation, and audit readiness possible. You will use AI-assisted development tools (code generation, copilots, large language models) as part of your everyday build process.

What You’ll Do

Hands-On Building & Upstream Data Cleanliness (~50%)

• Design and develop data analytics tools, automated validation frameworks, and dashboards that give Finance Operations and Controllership real-time visibility into data health across enterprise systems. Use AI to rapidly prototype, test, and deploy these solutions.

• Drive upstream data hygiene cross-functionally: partner with source-system owners in Revenue Operations, Procurement, Human Resources, and Engineering to fix data issues where they originate, not after they propagate.

• Own data dictionaries, lineage documentation, and quality scorecards for critical controllership data assets. Establish and enforce master data management (MDM) standards.

• Partner with the Chief Information Officer (CIO) and Information Technology (IT) on integration strategy, ensuring seamless data flows between ERP, sub-ledgers, and the enterprise data platform. Support Snowflake data warehouse deployment.

Mergers & Acquisitions Data Integration

• Lead data workstreams for M&A transactions end-to-end: perform data due diligence on target companies, assess data quality risks, and build integration playbooks for onboarding acquired-company data into Axon’s enterprise platform.

• Design and execute data mapping, cleansing, and migration plans for post-acquisition integration—ensuring acquired entities are reporting on clean, consolidated data within defined timelines.

• For interim stage prior to M&A integration, build, own, and operate extract-transform-load (ETL) and extract-load-transform (ELT) pipelines that remediate data quality issues at the source—before data reaches downstream AI models, reporting, or analytics. Leverage AI-assisted development tools (copilots, code generation, large language models) to accelerate pipeline development and iteration.

• Build repeatable M&A controllership data integration frameworks—using AI to automate data profiling, matching, and anomaly detection—that scale as Axon’s acquisition pace accelerates.

Financial Controls, SOX & Audit Readiness

• Co-design data pipelines and analytics with auditability built in—traceable lineage, complete audit trails, and evidence that holds up under external audit.

• Build or collaborate with process owners to build close-support tools (GL-to-sub-ledger, intercompany, journal entries) that reduce manual effort and strengthen control evidence.

Enabling AI Builders & Process Owners

• Serve as the data enablement partner to Axon’s Controllership AI team and Controllership process owners—ensuring they have access to clean, well-structured, governed datasets for machine learning (ML), automation, and large language model (LLM) initiatives.

• Collaborate with AI builders to define data requirements, validate input data quality, and create feedback loops that continuously improve data upstream of AI/ML workflows.

• Create self-service analytics capabilities that enable FP&A, Tax, Treasury, and Controllership teams to access trustworthy data without bottlenecks.

Partnership & Cross-Functional Leadership

• Serve as a trusted partner to the CIO, shaping technology roadmaps, enterprise architecture, and system integration decisions. Act as a strong ally to Controllership and Finance Operations.

• Engage stakeholders across FP&A, Tax, Treasury, Engineering, Product, Revenue Operations, and Legal to manage cross-functional data projects end-to-end. Influence without authority across global, distributed teams.

What You Bring

• Bachelor’s degree in Data Science, Computer Science, Statistics, Mathematics, Economics, Finance, or a related field with 8+ years in data science, data engineering, or analytics.

• Hands-on builder: strong, current proficiency with Structured Query Language (SQL) and Python—you write code, build pipelines, and ship tools, not just direct others. Comfortable using AI-assisted development tools to multiply your output.

• Deep experience with upstream data quality remediation, master data management, and data governance operationalization in a finance or accounting environment.

• Demonstrated M&A data integration experience: due diligence, data mapping, migration, and post-acquisition consolidation.

• Ability to build senior-level relationships, lead cross-functional projects end-to-end, and influence without direct authority across global teams.

• Working knowledge of US GAAP accounting processes (R2R, O2C, P2P, revenue recognition) or FP&A processes (budgeting, forecasting, variance analysis)—you understand the business logic, not just the data.

• Practical familiarity with SOX compliance and IT General Controls (ITGCs) sufficient to design audit-ready data pipelines, maintain traceable audit trails, and support internal audit teams and external auditors with data extracts, population listings, and control evidence—without needing to own the SOX program or control design.

Preferred Qualifications:

• Snowflake or comparable cloud data warehouse experience. Business intelligence (BI) platforms such as Sigma.

• High-growth, publicly traded technology company or digital transformation environment.

• Experience enabling AI/ML teams with clean data pipelines. Demonstrated use of AI code-generation in day-to-day development. Supervisory experience leading data teams.

• M&A integration at a company with an active acquisition strategy. Public safety, defense, or regulated industry background.

• Experience with audit management or financial close platforms/ERP and their data integration requirements; familiarity with how these tools consume and produce audit evidence.

Benefits that Benefit You

• Competitive salary and 401k with employer match
• Discretionary paid time off
• Paid parental leave for all
• Medical, Dental, Vision plans
• Fitness Programs
• Emotional & Mental Wellness support
• Learning & Development programs
• Employee Resource Groups (ERGs)
• And yes, we have snacks in our offices

Benefits listed herein may vary depending on the nature of your employment and the location where you work.

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.

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

The Company collects and uses Personal Information for human resources, employment, benefits administration, and business-related purposes.  To comply with our regulatory obligations under the California Consumer Privacy Act (“CCPA”), the Company is required to notify you of the Personal Information we collect.  To access our CCPA Policy including the categories of Personal Information we collect and the purposes for which we intend to use this information, please visit SEI's Privacy Policy.