Data Engineering Tech Lead – LatAm Only

This is a fully remote position, open to applicants in Argentina, +3 more countries.

📋 Description

• Act as the senior technical authority for R2’s data platform while leading the Data Engineering team on a daily basis.

• Report directly to the Director of Data Management.

• Take ownership of the architecture, technical roadmap, tools, vendor choices, reliability, and cost for the platform that supports data ingestion, processing, underwriting, and the enterprise data warehouse.

• Provide hands-on leadership in technical direction and standards as a lead engineer.

• Manage team planning, prioritization, and delivery.

• Gradually oversee Senior Data Engineers, conducting 1:1 meetings, performance evaluations, and career development discussions.

• Define and manage the target architecture for data ingestion, cleaning, processing, warehouse operations, Airflow orchestration, and underwriting data flows.

• Establish and maintain the Data Engineering technical roadmap.

• Assess and choose tools and vendors, providing input on contracts.

• Design a multi-country, multi-entity platform including a fully isolated EU data platform and compliance with data residency regulations.

• Remain actively engaged with Snowflake, Airflow DAGs, dbt, and Python.

• Ensure the reliability, observability, and SLAs of production pipelines.

• Develop on-call rotation, incident response strategies, and post-mortem practices.

• Manage Snowflake expenditures through warehouse sizing, usage monitoring, budgeting, and cost optimization.

• Define and uphold standards for modeling, testing, CI/CD, documentation, and code reviews.

• Implement AI-enhanced tools and agents to improve productivity and data operations.

• Oversee data initiatives from start to finish, including scoping, estimation, planning, tracking, and communication with stakeholders.

• Mentor and develop Senior Data Engineers through design and code reviews, along with ongoing feedback.

• Engage in hiring processes, onboarding, and team structure development.

• Collaborate with Analytics, Product, Risk and Credit, ML, Engineering, and Compliance teams.

• Share ownership of data governance, encompassing data quality, lineage, cataloging, and access control.

• Design protocols for PII classification, masking, encryption, Snowflake role-based access, retention, and deletion.

• Ensure adherence to regulatory and audit compliance, including GDPR, LGPD, central bank regulations, and local reporting requirements, as well as investor and partner obligations.

• Convert regulatory requirements into technical controls, audit evidence, and documentation.

⛳️ Requirements

• 8–12+ years of experience in Data Engineering or closely related fields.

• Previous experience in a Principal or Staff Data Engineer role, or as a Tech Lead managing a team of four or more engineers.

• Demonstrated team leadership and project management skills.

• Extensive, hands-on production experience with Snowflake, including architecture, performance tuning, cost management, and role-based security; essential.

• Advanced practical experience with Airflow and dbt.

• Strong software engineering foundation with significant expertise in Python.

• Proficient in SQL and dimensional/analytical data modeling.

• Hands-on experience with ELT methodologies and tools such as Airbyte or Fivetran.

• Experience managing data platforms on AWS.

• Proven experience in building or operating data platforms across multiple countries, legal entities, or regulatory environments; essential.

• Practical knowledge of GDPR or LGPD and implementing governance controls for PII.

• Experience with monitoring, alerting, and incident response for production systems.

• Capability to clearly explain technical trade-offs to leaders and partners in Risk, Product, and Compliance.

• Proficient in English, with additional skills in Spanish or Portuguese.

• Snowflake experience is mandatory; profiles focused on Databricks or BigQuery without substantial production Snowflake experience will not be suitable.

• Bonus: experience in fintech, lending, credit risk, or underwriting data.

• Bonus: experience establishing an EU or isolated regional data platform with strict data residency requirements.

• Bonus: familiarity with data cataloging, lineage, or data contract tools.

• Bonus: experience integrating AI/ML tools or agents into data workflows or constructing ML feature pipelines.

• Bonus: experience designing self-serve analytics platforms.

• Bonus: experience with large-scale cloud data cost management (FinOps).

🏝️ Benefits

• Eligible team members have the opportunity to participate in R2’s Phantom Share Program, a performance-based incentive aligned with the long-term success and value creation of the company.

• Engage in a high-impact, mission-driven fintech environment.

• Experience ownership and impact within a fast-paced, growth-oriented startup.

• Collaborate cross-functionally with exceptional teams.

• Gain exposure to complex regulatory challenges and innovations in embedded finance.