Head of Data

Marathon Talent; Bogotá; On-site; COP 35,000,000 - 75,000,000; Full time

Job summary

Marathon Talent is seeking a Head of Data in Bogotá, Colombia, to own the data platform end-to-end and turn data into a competitive advantage across the full credit lifecycle. You will lead a diverse team of analytics, data engineering and data science professionals, building scalable pipelines and defining data strategy for AI-enabled lending applications.

The role requires 8+ years in data with 3+ years leading teams, hands-on SQL/Python, and experience with modern data stacks.

Qualifications

• 8+ years of experience in data with 3+ years leading data teams
• Proven track record building data warehouses and pipelines
• Experience delivering AI/LLM use cases and data governance
• Strong executive communication with leadership and investors

Responsibilities

• Define and execute the data roadmap aligned with business goals
• Lead analytics engineering, data engineering and data science teams
• Own BigQuery warehouses and data pipelines including CDC
• Shape data governance, quality, and security practices
• Prepare data for AI/LLM consumption and pricing/credit analytics
• Collaborate with product, finance and engineering to drive impact

Skills

Data strategy

Team leadership

Executive communication

Analytical mindset

Decision making under uncertainty

Education

Bachelor's in Engineering/CS/Economics

Master's degree (preferred)

Tools

BigQuery

dbt/Dataform

PostgreSQL

MongoDB

Job description

Company Overview

We are a fast-growing fintech, founded in Colombia by a team with extensive experience in both lending and technology. We provide top-tier credit products and technology solutions with a user-focused approach, ensuring quick and efficient loan origination. Our mission is to offer the best lending experience in the market.

Role Overview

We are seeking an experienced Head of Data to own our data platform end to end and turn it into a competitive advantage across the full credit lifecycle, from broker acquisition and origination to underwriting, servicing and collections. Reporting to the VP of Product & Data, you will build the data foundations, make our data ready for AI and LLM consumption, and lead the high-impact projects in pricing, credit risk, growth and operational efficiency. The ideal candidate is a builder who leads: hands-on enough to model a warehouse and ship a model, senior enough to set the data strategy, build the team and present to executive leadership and funding partners.

Key Responsibilities

• Data Strategy & Leadership: Define and execute the data roadmap, prioritized by business value, and build and lead the data team (analytics engineering, data engineering and data science).
• Data Warehouse & Infrastructure: Own our BigQuery warehouse and MongoDB/Postgres CDC pipelines. Build certified gold layers, immutable snapshots, data contracts, quality tests and freshness SLAs.
• Semantic Layer & Metrics: Establish a single, documented definition for every core metric (origination funnel, conversion, delinquency, vintages) shared by BI, finance and AI tools.
• AI & LLM Data Readiness: Prepare data across every stage of the credit lifecycle for LLM consumption: machine-readable data dictionaries, PII redaction, structured document and conversation data, versioned RAG corpora and evaluation frameworks.
• AI Agents & Operational Efficiency: Partner with product and engineering to deploy AI agents in onboarding, customer service and collections, measuring their impact on cost and service levels.
• Credit Risk & Pricing Analytics: Lead the evolution of default prediction and underwriting models (including reject inference and bureau data) and risk-based pricing, validated through controlled experiments.
• Growth & Distribution Analytics: Build predictive models for our broker network (activation, churn and productivity) to prioritize commercial efforts and increase origination.
• Funding & Investor Reporting: Deliver reproducible, auditable loan tapes, borrowing base and covenant reports for warehouse lenders and investors, reconciled with accounting.
• Data Governance & Compliance: Ensure data practices comply with Colombian regulation (Ley 1581 on personal data, Ley 1266 on credit bureau reporting) and support ISO 27001 controls.
• Experimentation & Data Culture: Make A/B testing the default for product and pricing decisions, and enable self-serve analytics across the company.

This role is a critical leadership position within our company, with the opportunity to shape how data and AI power every lending decision we make. If you are a builder who thrives at the intersection of data platforms, credit and AI, we'd love to hear from you!

• Based in Bogotá, Colombia.
• 8+ years of experience in data, with at least 3 years leading data teams, preferably in fintech, lending or banking.
• Hands-on expertise in SQL and Python, and in modern data stack tools (BigQuery or similar cloud warehouse, dbt or Dataform, orchestration).
• Proven experience designing a data warehouse from operational sources, including CDC pipelines, dimensional modeling and data quality frameworks.
• Track record of taking predictive models (credit risk, propensity or pricing) from analysis to production, with monitoring in place.
• Experience delivering AI or LLM use cases in production, including retrieval, evaluation and data privacy controls.
• Excellent executive communication, with the ability to present to leadership committees, investors and funding partners.
• Ability to operate in highly uncertain environments and make decisions with incomplete information.
• Bachelor's degree in Engineering, Statistics, Computer Science, Economics or a related quantitative field.

Preferred Qualifications

• Experience with payroll and pension deducted loans (PDL) or other structured loan products.
• Familiarity with Colombian financial and data regulations (SFC, SIC, Ley 1581, Ley 1266).
• Experience building loan tapes and covenant reporting for warehouse facilities or securitizations.
• Experience with experimentation platforms and causal inference.
• Master's degree in a quantitative field.
• Experience scaling data functions in a startup environment.