Director of Data & Analytics

Job Description

Job Description

Position: Director of Data & Analytics

Location: Remote within the US, or hybrid from Fort Lauderdale, FL / Dallas, TX / Chicago, IL / Columbus, OH

Status: Full Time, W2

Reports to: Chief Operating Officer

Direct report: Senior Data Engineer

Salary Range: $185,000.00 to $210,000.00 annually, plus a 10–20% target bonus

Dress code: Business Casual, Casual Fridays

About Us

Fuego Leads is looking for a highly motivated Director of Data & Analytics to join our team. We are a technology-focused health insurance company. We generate consumer demand through our own websites and national advertising, operate our own agency and call center, and distribute leads and live call transfers to the partners who buy from us. We are also building a direct-to-consumer brand of our own.

We build our own technology. Our engineering team has developed proprietary dialing, SMS, and call center systems, along with quoting tools and the agent-facing interfaces our agency runs on.

Our philosophy is to provide a quality service to our clients, offering an easy and seamless experience from start to finish. Compliance and customer experience are treated as core to the business rather than as constraints on it.

Founded in 2019, Fuego is headquartered in Fort Lauderdale, Florida, with shared office space in Chicago, Illinois and Columbus, Ohio.  At Fuego Leads, we recognize that our most valuable asset is our people. We prioritize creating an inclusive and diverse workforce, where every individual feels valued, respected, and empowered.

The Opportunity

Fuego's data function is moving from business reporting to the operational layer that executive decisions, marketing programs, and our AI systems run on. This role owns that layer end to end: the architecture, the definitions, the models, and the roadmap — and builds it hands-on through the first year.

Our stack today runs on SQL Server in production with BigQuery as the warehouse, and reporting across both an in-house application and Sigma. You'll set the target-state design and sequence the work to get there.

What you'll own

• Core metric definitions — lead, contact, conversion, placement, CAC, LTV — including the calculations, the governance, and a named owner for each.

• A certified core layer in BigQuery covering lead lifecycle, call and contact activity, agent and team performance, and media and channel spend, with exec-level reporting running on it.

• The target-state data architecture across source systems, warehouse, and transformation layer, plus the data engineering roadmap that delivers it.

• Multi-touch attribution across acquisition channels, resolved through to policy outcome and accurate enough to reallocate media and partner spend on.

• A unified customer database, with identity resolved across systems into one durable record — the basis for LTV, renewals, persistency, cross-sell, and lifecycle marketing.

• Fuego's ML roadmap — scoring, prioritization, routing — along with the platform to develop, deploy, monitor, and retrain on. Model work sits with an external vendor and a senior data engineer today; you'll bring it in-house and own model quality.

• The data layer our AI systems retrieve from: schemas, identity resolution, and real-time availability. Every call is captured as a transcript with LLM scorecard values on top, and those need to be modeled and joined to customer, lead, and agent records.

• Lead-quality economics, measured from acquisition cost through downstream buyer outcome.

• Technical evaluation of AI platforms and vendors for the business more broadly.

How you'll work

This is a small team by design, and the expectation is that it operates like a larger one, incorporating  AI tooling into how the function delivers, from transformation authoring and testing through documentation and agent workflows. You'll also own the call on how the business consumes insight, which we expect to look less like dashboards someone has to remember to open and more like trusted data available where work already happens.

One senior data engineer reports to you on day one. You'll report to the COO and work directly with exec staff, marketing, and engineering — translating what the data layer can and can't support into decisions the exec team can act on. Through year one you'll be writing transformations, reviewing models, and in the warehouse yourself.

What You Bring to the TableRequired

• 8+ years in data and analytics, including ownership of the design of a production warehouse and transformation layer, not only work within someone else's.

• Expert SQL and production Python — pipelines, model code, and automation that other people depend on.

• A modern transformation framework such as dbt, and the engineering practice that comes with it: version control, testing, code review, and documented lineage.

• Managed a cloud warehouse run in production. BigQuery is ours; Snowflake, Redshift, or Databricks translate.

• Models you've deployed and kept running, including monitoring and retraining.

• Multi-touch attribution you've built and put in front of a media budget, and customer identity resolution across systems that weren't designed to share a customer record.

• Substantive use of AI tooling in your own delivery. Be ready to walk us through something specific you built with it and where you stopped trusting it.

• Effective written communication where  an exec can read your recommendation once and act on it.

You'll do well here if…

• You've built new capability and cleaned up what came before it on the same timeline.

• You've built a data layer that an AI or LLM application retrieves from, and you know how that differs from designing for a dashboard.

• You'd rather prototype something in a week and learn from it than scope it for a quarter.

• You're happy owning scope rather than headcount. One person reports to you today, and the team grows with what you build.

• You've held a metric definition against a team that preferred a different number, and kept the working relationship.

Location & Hours

• This role can be based remotely within the United States, or hybrid from the Fort Lauderdale, Dallas, Chicago, or Columbus metro areas.