Technical Coordinator, Data Creators

About the role

This position turns raw information into decisions for the Data Creators team at Figure. You will own the coordination of data projects from intake through delivery, ensuring that analysts, data scientists, and data engineers have clean requirements and structured inputs. You will act as the central point of contact between the Data Creators group and hardware and engineering teams located in the United States. In this role, you will design and maintain workflows that transform messy inputs into dashboards, models, and pipelines that the business can trust. You will translate ambiguous requests into clear data tasks and manage the lifecycle of each analysis with rigorous documentation. You will partner closely with Project Coordinators and Shift Coordinators to keep timelines on track and stakeholders aligned. Your work will directly support rapid growth initiatives at Figure by making sure data teams can focus on analysis instead of coordination overhead. A strong portfolio of past analyses and operational impact will matter more than degrees in many hiring decisions for this track.

Key facts

What you'll do

Coordinate intake sessions with business stakeholders to clarify objectives and success metrics for data projects.

Translate ambiguous requests into structured data tasks that analysts, data scientists, and data engineers can execute.

Maintain a living inventory of data assets, definitions, and ownership to reduce confusion across teams.

Build and update project documentation, including timelines, dependencies, and decision logs for each initiative.

Manage the flow of information between the Data Creators team in Mexico City and hardware and engineering teams in the United States.

Track project status, surface risks early, and coordinate adjustments to schedules and priorities as conditions change.

Support the design of metrics and experiments, ensuring that data requirements are feasible and well documented.

Perform data quality checks and sanity checks on outputs before results are shared with decision makers.

Organize and maintain templates for analyses, code snippets, and communication artifacts used across the data function.

Solicit feedback from data scientists, analysts, and engineers to continuously improve tooling and workflows.

Serve as the first line of escalation for data-related questions, routing issues to the appropriate specialist as needed.

Own end to end coordination of at least one major data project from discovery through deployment and post mortem review.

Maintain a clear and up to date view of priorities, blockers, and dependencies using project management tools.

Act as a bridge between technical teams and business stakeholders to ensure that insights are actionable and understood.

Requirements

You must be eligible to work in Mexico City without sponsorship, as the role is based in Mexico City and does not require relocation.

You must have the legal right to work in Mexico without requiring company sponsorship.

You must be fluent in English, as you will coordinate with hardware and engineering teams in the United States on a regular basis.

You must have strong written and verbal communication skills in English to clearly articulate requirements and updates.

You must be comfortable working in a fast paced environment where priorities can shift quickly.

You must be highly organized and able to manage multiple projects and deadlines simultaneously.

You must be detail oriented and able to maintain accurate records of decisions, dependencies, and timelines.

You must be proactive in identifying risks and raising issues before they impact delivery.

Nice to have

Hands-on experience with VR/AR headsets, motion capture systems, robotics, or drones.

Experience in startups of rapid growth.

Skills & tools

SQL or a querying language for data platforms.

Experience with dashboards and visualization tools.

Comfort with statistical concepts and basic modeling.

Familiarity with software development practices and version control.

Experience with project management tools and documentation platforms.

Practical notes

Typical interview steps

Data interviews commonly include a SQL or coding exercise, a statistics question, and a case study. Candidates may be asked to design a metric, interpret an experiment, or build a small model. Some companies give a take-home analysis. Expect questions about past projects and the business impact of your work. Interviewers often evaluate how you communicate uncertainty and business impact, not only the math. Bringing a clean write-up of a past analysis to the interview is well received.

Career growth

Data careers grow toward senior analyst, staff data scientist, or data engineering lead. Many professionals specialize in machine learning, analytics, or infrastructure. Cross functional work with product and engineering teams becomes more important at senior levels. The field changes quickly, so continuous learning is part of the job. Professionals who can translate numbers into decisions tend to advance fastest.

Questions to ask

Worth asking in any interview: how the team measures success, who the role works with daily, what the onboarding looks like, and what the company is trying to achieve this year. Asking what past hires did well is a strong final question. Keep the list short and pick the questions that matter most to you.

About the company

See how a Home Equity Line of Credit with Figure can help you plan a home renovation project, consolidate high-interest debt, or fund your dream vacation!

About the location

Latin America's largest metro has a massive coworking scene. Monthly costs around $1,400. Roma, Condesa, and Polanco are the main neighborhoods. Altitude (2,240m) keeps temps around 16-25°C year-round. Metro covers the city.