What is Cobre, and what do we do?

Cobre is Latin America’s leading instant b2b payments platform. We solve the region’s most complex money movement challenges by building advanced financial infrastructure that enables companies to move money faster, safer, and more efficiently.

We enable instant business payments—local or international, direct or via API—all from a single platform.

Built for fintechs, PSPs, banks, and finance teams that demand speed, control, and efficiency. From real-time payments to automated treasury, we turn complex financial processes into simple experiences.

Cobre is the first platform in Colombia to enable companies to pay both banked and unbanked beneficiaries within the same payment cycle and through a single interface.

We are building the enterprise payments infrastructure of Latin America!

What we are looking for:

Cobre is seeking a Customer Support Automation Engineer to architect and deliver robust, production-grade data solutions that boost efficiency, resilience, and scalability across our financial-operations, fraud-risk, and customer-service ecosystems. You’ll partner closely with client success to turn raw data into reliable, actionable insights that power day-to-day execution and long-term strategy and to automate time consuming tasks that represent bottle necks for scalability within the team. The ideal candidate is a hands-on technical expert who thrives on solving business problems and automation—and who uplifts teammates through knowledge-sharing.

To promote faster collaboration and maintain the highest standards, this role will also have a dotted-line reporting relationship with the core data team leadership responsible for data engineering, analytics, and AI.

What would you be doing:

• Process automation: Design, develop, and deploy scalable automation pipelines that eliminate manual, repetitive tasks using Python, SQL, APIs, RPA tools (e.g., UiPath, Power Automate), and orchestration frameworks (e.g., Airflow, n8n).
• Technical strategy & Execution: Contribute to analytics roadmaps, tool selection, and resource planning aligned with Cobre’s objectives. Identify and prototype AI-driven opportunities (e.g., ML anomaly detection, predictive forecasting). Present technical approaches and project status to senior stakeholders with clarity and candor.
• Analytics Architecture & Data Modeling: Design and maintain scalable data pipelines, ETL/ELT workflows, and transformation layers (dbt) that power operational analytics. Define and enforce modeling standards, naming conventions, and documentation practices. Collaboration with Data Engineering & Infrastructure: Work closely with Data Engineering to align on infrastructure needs, cost-efficient architectures, and emerging tech (e.g., streaming, advanced analytics frameworks). Partner with domain teams to define key metrics, semantic layers, and self-service analytics processes—maintaining clear data dictionaries and documentation.
• Technical mentorship: Share best practices, perform code reviews, and coach peers in SQL, dbt, and automation techniques—elevating data literacy across client success without formal line-management duties.

What do you need:

• Educational Background: Bachelor’s or Master’s in Computer Science, Data Engineering, Information Systems, Mathematics, or related field.

Technical Proficiency:

• Expert-level SQL and hands-on experience with modern warehouses (Snowflake, Redshift, Databricks, etc.).
• Proven track record building ETL/ELT pipelines with Airflow, dbt, or similar frameworks. Knowledge n8n.
• Strong background in data-modeling techniques (dimensional, star schemas) and data-governance best practices.
• Proficiency in Python for data engineering and automation; familiarity with APIs and RPA tools.
• Experience with BI/visualization tools (Sigma, Looker, Tableau, Power BI) and self-service analytics principles.
• Knowledge of Streamlit a plus.
• Exposure to real-time streaming platforms (Kafka, Kinesis) desirable.
• Project and stakeholder Management
• Demonstrated ability to lead complex analytics projects end-to-end, balancing speed, scalability, and data quality.
• Skilled at translating business requirements into technical specifications and communicating results to non-technical audiences.

Soft Skills

• Exceptional problem-solving, analytical thinking, and attention to detail.
• Strong written and verbal communication; adept at partnering with cross-functional teams.
• Passion for mentoring and fostering a culture of curiosity, innovation, and continuous improvement.

Preferred qualification:

• Experience in financial services, banking, or payments, with awareness of regulatory/fraud considerations.
• Experience in automation is preferred. If that automation is in Client Success related tasks it is a plus.
• Familiarity with AI/ML techniques (fraud detection, customer segmentation) and AI-agent frameworks.