Sr Marketing Analytics Engineer

What is Cobre and what do we do?

Cobre is a corporate treasury and payments platform designed to elevate the way Latin American companies manage their finances. At Cobre, we build CFO-tech on top of owned payment rails in order to give real-time capabilities to domestic and cross border payments, empowering every peso that our clients move.

We are committed to eliminating friction between companies, their banking partners, their people and their money so that money movement becomes a growth driver, rather than a time-consuming task. In this pursuit, Cobre has grown to become a trusted provider of corporates and tech giants in the region, while building a profitable business that has grown 10x in the past 12 months.

What we are looking for

Cobre is seeking a forward-thinking Senior Marketing Analytics Engineer, reporting to the Head of Marketing, to drive the design, development, and optimization of our marketing analytics stack. In this role, you will work with cross-functional teams—including Marketing, Product and Data —to transform complex marketing data into actionable insights. You will be instrumental in shaping our marketing data infrastructure, ensuring high data quality, and unlocking insights that fuel Cobre’s growth.

This role will also collaborate closely (dotted-line) with our core data team—responsible for data engineering, analytics, and AI—to align on best practices, promote knowledge sharing, and maintain a unified analytics vision across the organization.

What would you be doing

Marketing Data Architecture & Integrations

• Design scalable end-to-end pipelines (dbt, Airflow, Snowflake) to unify and integrate data from HubSpot, Salesforce, and ad networks.
• Develop and optimize data models to enhance the availability and quality of insights for sales and marketing teams.
• Incorporate lead intelligence platforms (Apollo, Lusha, Sales Navigator) to enrich contact records, ensuring accurate and data-driven decision-making.
• Focus on seamless integration and efficient data modeling to improve marketing and sales strategies.

Collaboration with cross functional teams

• Partner with Marketing and Growth teams to understand strategic objectives, key metrics, and analytics requirements.
• Work closely with Data Engineering to define infrastructure needs (e.g., storage, processing, security) and align on scalable, cost-effective solutions.

Advanced Marketing Analytics

Utilize advanced analytic and modeling techniques to improve attrition, funnels, and channel performance such as:

• Implement multi-touch attribution models (e.g., logistic regression, Markov chains, survival analysis) to assign channel credit.
• Use time-series forecasting (ARIMA, Prophet) and machine learning (Random Forest, GBM..) to predict behavior and outcomes.
• Apply clustering (K-means, hierarchical) for precise customer segmentation.
• Utilize NLP for sentiment analysis and insights from social feedback.
• Deploy uplift modeling to optimize targeting by measuring campaign impact.

Technical Leadership & Mentorship

• Mentor junior engineers on best practices
• Optimize pipeline performance, and champion data governance.

Strategic Planning & Execution

• Identify new AI/ML opportunities
• Communicate roadmaps and progress
• Drive continuous improvement in marketing analytics.

What do you need

• Educational Background: Bachelor’s or Master’s in Computer Science, Data Engineering, Statistics, Marketing Analytics, or a related field.
• Technical Proficiency: Advanced SQL and Python, modern data warehousing (Snowflake, Redshift, or Databricks), Data models design, storage cloud services (S3), ETL/ELT (Airflow, dbt), and BI tools (Looker, Tableau).
• Marketing Analytics: Experience with marketing technology ecosystems (e.g., HubSpot, Salesforce, ad-tech integrations, or lead enrichment tools like Apollo/Lusha) is a plus.
• Analytics Ecosystem Knowledge In-depth understanding of analytics engineering processes, testing frameworks, and data validation strategies. Ability to translate marketing goals into technical specifications that drive business impact. Understanding of AI Ecosystem and AI Agents for Marketing is a plus.
• Soft Skills: Strong communication, stakeholder management, analytical thinking, and mentorship experience.
• Nice to have: FinTech/banking experience, AI/ML exposure, Agile methodologies.