Latitude AI (lat.ai) develops automated driving technologies, including L3, for Ford vehicles at scale. We’re driven by the opportunity to reimagine what it’s like to drive and make travel safer, less stressful, and more enjoyable for everyone.  

When you join the Latitude team, you’ll work alongside leading experts across machine learning and robotics, cloud platforms, mapping, sensors and compute systems, test operations, systems and safety engineering – all dedicated to making a real, positive impact on the driving experience for millions of people. 

As a Ford Motor Company subsidiary, we operate independently to develop automated driving technology at the speed of a technology startup. Latitude is headquartered in Pittsburgh with engineering centers in Dearborn, Mich., and Palo Alto, Calif.

Meet the team:

The Autonomy Analytics team is responsible for evaluating the performance of our autonomous software using data, statistics, and machine learning. Combining data from real-world testing with our extensive simulations, our team builds the metrics and analytics that ensure our product is safe, reliable, and delights our customers. 

Our team is spread geographically with some members on-site in Pittsburgh, Palo Alto, and Dearborn. Others work fully remotely.

What you’ll do: 

• Translate loosely defined questions into clear requirements, metric definitions, and analytical deliverables
• Partner closely with software development teams, test engineering, product, and analytics partners to understand needs and deliver trusted data products
• Build and maintain scalable data models in Google BigQuery and similar cloud data platforms to support reporting, analysis, and operational decision-making
• Develop dashboards and lightweight data applications in Apache Superset, Plotly Dash, or similar tools for technical and business stakeholders
• Investigate source data, identify quality issues, and implement durable fixes that improve accuracy, consistency, and reliability
• Create reusable datasets, testing practices, and documentation that strengthen trust in data and improve self-service access
• Balance near-term dashboard development with long-term data modeling work to support both speed and scale
• Communicate findings, assumptions, and tradeoffs clearly to internal stakeholders and external platform or data partners as needed

What you'll need to succeed:

• Bachelor's degree in Computer Engineering, Computer Science, Electrical Engineering, Robotics or a related field and 4+ years of relevant experience (or Master's degree and 2+ years of relevant experience, or PhD)
• Experience building and maintaining analytics-ready data models in Google BigQuery or a similar cloud data warehouse
• Experience using dbt or a similar data transformation framework to develop tested, documented, and maintainable data pipelines
• Experience designing dashboards and analytical applications in Apache Superset, Tableau, or similar reporting and visualization tools
• Strong SQL skills, including complex transformations, data validation, and query optimization
• Experience with Python for data analysis and application development, including the ability to contribute to and maintain Plotly Dash dashboards
• Demonstrated ability to succeed in ambiguous environments by defining requirements, shaping metrics, and creating structure from incomplete problem statements
• Experience partnering with software development, test engineering, product, or similar cross-functional teams to deliver measurable outcomes
• Strong foundation in data modeling, dashboard design, documentation, and quality assurance practices
• Strong written and verbal communication skills with the ability to explain analytical concepts and findings to varied audiences

Nice to have: 

• Experience supporting autonomous vehicle development or other complex hardware and software products
• Experience working with telemetry, operational, or product usage data at scale
• Experience building shared metrics and self-service reporting solutions for engineering and product organizations
• Experience with front-end technologies such as HTML, CSS, JavaScript, or React to support customization and enhancement of data applications and dashboards

What we offer you:

• Competitive compensation packages
• High-quality individual and family medical, dental, and vision insurance
• Health savings account with available employer match
• Employer-matched 401(k) retirement plan with immediate vesting
• Employer-paid group term life insurance and the option to elect voluntary life insurance
• Paid parental leave
• Paid medical leave
• Unlimited vacation
• 15 paid holidays
• Daily lunches, snacks, and beverages available in all office locations
• Pre-tax spending accounts for healthcare and dependent care expenses
• Pre-tax commuter benefits
• Monthly wellness stipend
• Adoption/Surrogacy support program
• Backup child and elder care program
• Professional development reimbursement
• Employee assistance program
• Discounted programs that include legal services, identity theft protection, pet insurance, and more
• Company and team bonding outlets: employee resource groups, quarterly team activity stipend, and wellness initiatives

Learn more about Latitude’s team, mission and career opportunities at lat.ai!

The expected base salary range for this full-time position in California is $179,200 - $268,800 USD. Actual starting pay will be based on job-related factors, including exact work location, experience, relevant training and education, and skill level. Latitude employees are also eligible to participate in Latitude’s annual bonus programs, equity compensation, and generous Company benefits program, subject to eligibility requirements.

Candidates for positions with Latitude AI must be legally authorized to work in the United States on a permanent basis. Verification of employment eligibility will be required at the time of hire. Visa sponsorship is available for this position.

We are an Equal Opportunity Employer committed to a culturally diverse workforce. All qualified applicants will receive consideration for employment without regard to race, religion, color, age, sex, national origin, sexual orientation, gender identity, disability status or protected veteran status.

Latitude AI (lat.ai) develops automated driving technologies, including L3, for Ford vehicles at scale. We’re driven by the opportunity to reimagine what it’s like to drive and make travel safer, less stressful, and more enjoyable for everyone.  

When you join the Latitude team, you’ll work alongside leading experts across machine learning and robotics, cloud platforms, mapping, sensors and compute systems, test operations, systems and safety engineering – all dedicated to making a real, positive impact on the driving experience for millions of people. 

As a Ford Motor Company subsidiary, we operate independently to develop automated driving technology at the speed of a technology startup. Latitude is headquartered in Pittsburgh with engineering centers in Dearborn, Mich., and Palo Alto, Calif.

Meet the team:

As Latitude’s Data Platform team, our mission is to build the scalable, high-performance infrastructure that turns structured data into insight to drive Latitude’s business forward. We provide foundational solutions for handling, processing and visualizing large-scale data to ensure every team at Latitude—from Autonomy to Machine Learning to Fleet Operations—can measure what matters.

We promote Data as a Product; this means applying rigorous software engineering discipline to data assets: versioning, public/private interfaces for data models, and a relentless focus on automated testing. To scale these principles across our org, we design self-service systems that prioritize continuous, iterative delivery, developer velocity, cost transparency and efficiency by default.

What you’ll do: 

In this role, you will help build and evolve:

• A High-Performance Cloud-Native Stack: Work with a blend of serverless cloud analytics tools and self-hosted Kubernetes deployments to serve a diverse range of internal stakeholders
• Abstracted Data Frameworks: Develop internal tooling that enables engineers to self-serve data loading and testing. You’ll work on systems capable of handling high-throughput, low-latency streaming and massively parallel bulk loads scaling to hundreds of terabytes daily, with robust support for generic and customer-defined data unit and integration testing and monitoring. You’ll work closely with teams such as Latitude’s Autonomy Analytics team, among many others, to understand and generalize platform feature needs and provide guidance/documentation on usage
• Open Source & Custom Tooling: We deploy and scale industry-leading data engineering and analytics tools. We lean into the open-source ecosystem, deploying and extending OS solutions such as dbt, Airflow and Superset to serve Latitude’s unique autonomy and ML use cases
• A Rich Metadata Layer: Provide the automation and cataloging tools that serve as the backbone for discovery and tracing. You will play a key role in enabling a well-documented data front ready for both human exploration and LLM/RAG-based consumption

What you'll need to succeed:

• Bachelor's degree in Computer Engineering, Computer Science, Electrical Engineering, Robotics or a related field and 2+ years of relevant experience, Master's degree, or PhD
• Software Craftsmanship: Strong Python development skills with a focus on SOLID design principles. You have experience managing the full lifecycle of internal packages, from intake and design to release and maintenance.
• Cloud & Infrastructure: Experience managing cloud infrastructure via Infrastructure as Code (IaC). You should be comfortable with Docker, Terraform, Kubernetes, Helm, and observability via Grafana or similar.
• Data Fluency: Understanding of SQL and OLAP concepts. You are familiar with the architecture of Massively Parallel Processing (MPP) systems (e.g., BigQuery, Redshift, or ClickHouse) and understand how to optimize for both performance and cost. Experience with dbt is a plus.
• Distributed Orchestration and Streaming: Familiarity with data orchestration tools (e.g., Airflow, Dagster) and a conceptual understanding of distributed stream processing (e.g., the Apache Beam model). You should understand challenges like watermarks, stateful processing, and temporal consistency.
• The "Internal Customer" Mindset: You are a product-minded engineer. You have the empathy to understand the pain points of your fellow engineers and the drive to build tools that are actually useful. You maintain a high bar for quality while prioritizing high-impact delivery.

Bonus Points:

• Automated Release Engineering: A standard-bearer for CI/CD excellence. You understand how to build robust Jenkins or GitHub Actions pipelines that automate testing, linting, and deployment, ensuring a high-velocity but safe development environment.
• Privacy & Security by Design: Experience with end-to-end security and isolation. You understand the importance of least-privilege access, service account management, and automated data anonymization/governance.

What we offer you:

• Competitive compensation packages
• High-quality individual and family medical, dental, and vision insurance
• Health savings account with available employer match
• Employer-matched 401(k) retirement plan with immediate vesting
• Employer-paid group term life insurance and the option to elect voluntary life insurance
• Paid parental leave
• Paid medical leave
• Unlimited vacation
• 15 paid holidays
• Daily lunches, snacks, and beverages available in all office locations
• Pre-tax spending accounts for healthcare and dependent care expenses
• Pre-tax commuter benefits
• Monthly wellness stipend
• Adoption/Surrogacy support program
• Backup child and elder care program
• Professional development reimbursement
• Employee assistance program
• Discounted programs that include legal services, identity theft protection, pet insurance, and more
• Company and team bonding outlets: employee resource groups, quarterly team activity stipend, and wellness initiatives

Learn more about Latitude’s team, mission and career opportunities at lat.ai!

The expected base salary range for this full-time position in California is $150,320 - $225,480 USD. Actual starting pay will be based on job-related factors, including exact work location, experience, relevant training and education, and skill level. Latitude employees are also eligible to participate in Latitude’s annual bonus programs, equity compensation, and generous Company benefits program, subject to eligibility requirements.

Candidates for positions with Latitude AI must be legally authorized to work in the United States on a permanent basis. Verification of employment eligibility will be required at the time of hire. Visa sponsorship is available for this position.

We are an Equal Opportunity Employer committed to a culturally diverse workforce. All qualified applicants will receive consideration for employment without regard to race, religion, color, age, sex, national origin, sexual orientation, gender identity, disability status or protected veteran status.

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.