Data Engineering Tech Lead

<h3>Accountabilities:</h3><li>
<strong>Data Platform Architecture and Technical Strategy:</strong>Own the end-to-end architecture of the data platform, covering data ingestion, cleansing, processing, warehousing, orchestration, and data flows supporting credit underwriting and analytics.</li><li>
<strong>Technical Direction and Roadmap:</strong>Partner with the Director of Data Management to establish architectural principles, define engineering standards, and develop a technical roadmap that balances business priorities, platform reliability, modernization, and technical debt.</li><li>
<strong>Technology and Vendor Management:</strong>Evaluate, select, and manage data engineering tools and vendors, contributing to technical assessments, purchasing decisions, and contract discussions.</li><li>
<strong>Multi-Country Platform Architecture:</strong>Design and scale data infrastructure across multiple countries and legal entities, including a fully isolated European data platform with appropriate data residency and regional separation controls.</li><li>
<strong>Hands-On Engineering:</strong>Remain actively involved in the most technically complex areas of the platform, particularly Snowflake architecture, Apache Airflow DAGs, dbt transformations, and Python-based data processing.</li><li>
<strong>Production Reliability and Observability:</strong>Own the reliability, monitoring, observability, and service-level agreements of production data pipelines, ensuring data systems remain available, accurate, and performant.</li><li>
<strong>Incident Management:</strong>Establish and maintain on-call rotations, incident response procedures, root cause analysis practices, and post-incident reviews to strengthen operational resilience.</li><li>
<strong>Performance and Cost Optimization:</strong>Manage Snowflake infrastructure costs through warehouse sizing, consumption monitoring, budgeting, resource optimization, and data platform FinOps practices.</li><li>
<strong>Engineering Standards and Quality:</strong>Define and enforce standards for data modeling, automated testing, continuous integration and deployment, documentation, and code reviews.</li><li>
<strong>AI-Enabled Engineering:</strong>Identify and implement AI-powered tools and agents where they can demonstrably improve engineering productivity, data operations, and workflow efficiency.</li><li>
<strong>Team Leadership and Delivery Management:</strong>Lead the Data Engineering team’s daily operations, including planning, prioritization, workload management, delivery schedules, and the resolution of technical blockers.</li><li>
<strong>Project and Stakeholder Management:</strong>Drive data initiatives from initial scoping and estimation through execution and delivery, communicating timelines, dependencies, risks, and technical trade-offs to relevant stakeholders.</li><li>
<strong>Mentoring and Team Development:</strong>Coach and develop Senior Data Engineers through architectural discussions, design reviews, code reviews, and ongoing feedback, progressively assuming direct people management responsibilities.</li><li>
<strong>Recruitment and Organizational Growth:</strong>Participate in hiring, onboarding, and defining the team's structure as the organization expands.</li><li>
<strong>Cross-Functional Collaboration:</strong>Partner with Analytics, Product, Risk and Credit, Machine Learning, Engineering, and Compliance teams to translate business needs into scalable data platform capabilities.</li><li>
<strong>Data Governance and Quality:</strong>Co-own data governance with the Director of Data Management, ensuring appropriate data quality, lineage, cataloging, access controls, and documentation.</li><li>
<strong>Privacy, Security, and Compliance:</strong>Design and enforce controls for personally identifiable information (PII), including classification, masking, encryption, role-based access, data retention, and deletion.</li><li>
<strong>Regulatory Readiness:</strong>Ensure the platform meets applicable regulatory, audit, and reporting requirements, including GDPR, Brazil's LGPD, local central bank requirements, and relevant investor and business partner obligations.</li><li>
<strong>Audit Documentation and Controls:</strong>Translate regulatory requirements into technical safeguards, documented processes, and verifiable evidence that support internal and external audits.</li><h2>Requirements:</h2><li>
<strong>Professional Experience:</strong>8–12+ years of experience in Data Engineering or a closely related discipline, with a demonstrated record of delivering and operating complex production data platforms.</li><li>
<strong>Technical Leadership:</strong>Previous experience as a Principal or Staff Data Engineer, or as a Tech Lead managing or guiding a team of at least four engineers.</li><li>
<strong>Team and Project Management:</strong>Proven ability to lead team delivery, manage multi-quarter initiatives, prioritize competing demands, coordinate stakeholders, and communicate project risks and trade-offs effectively.</li><li>
<strong>Advanced Snowflake Expertise:</strong>Extensive hands-on production experience with Snowflake, including architecture design, performance tuning, cost optimization, warehouse management, and role-based access control.<strong>Snowflake experience is mandatory.</strong>Candidates whose experience is primarily with Databricks or BigQuery without substantial Snowflake expertise will not be a fit.</li><li>
<strong>Airflow and dbt:</strong>Advanced production experience with Apache Airflow for workflow orchestration and dbt for data transformation, modeling, and testing.</li><li>
<strong>Software Engineering and Programming:</strong>Strong software engineering foundations, advanced Python proficiency, and excellent SQL skills, including experience with dimensional modeling and analytical data architecture.</li><li>
<strong>Data Integration and ELT:</strong>Practical experience implementing ELT patterns and using data ingestion and integration tools such as Airbyte or Fivetran.</li><li>
<strong>Cloud Infrastructure:</strong>Experience designing, deploying, and operating data platforms on AWS, including cloud infrastructure management and optimization.</li><li>
<strong>Multi-Region and Regulatory Architecture:</strong>Demonstrated experience building or operating data platforms across multiple countries, legal entities, or regulatory jurisdictions. This is a mandatory requirement.</li><li>
<strong>Data Privacy and Governance:</strong>Practical knowledge of data protection regulations such as GDPR and LGPD, with experience implementing governance frameworks and technical controls for sensitive and personally identifiable information.</li><li>
<strong>Production Operations:</strong>Comfort owning business-critical production systems, including monitoring, alerting, incident response, troubleshooting, and continuous reliability improvements.</li><li>
<strong>Stakeholder Communication:</strong>Ability to explain complex technical decisions and trade-offs clearly to senior leadership and non-technical partners in Risk, Product, and Compliance.</li><li>
<strong>Language Skills:</strong>Professional proficiency in English, together with Spanish or Portuguese, to collaborate effectively across international teams.</li><li>
<strong>Leadership and Collaboration:</strong>A proactive, hands-on approach to technical problem-solving, with strong mentoring, organizational, communication, and decision-making skills.</li><li>
<strong>Preferred Fintech Experience:</strong>Background in fintech, lending, credit risk, or data platforms supporting underwriting and financial services.</li><li>
<strong>Preferred Regional Platform Experience:</strong>Experience establishing an EU data platform or another isolated regional environment with strict data residency requirements.</li><li>
<strong>Preferred Governance Tooling:</strong>Familiarity with data cataloging, lineage management, and data contract tools.</li><li>
<strong>Preferred AI and Machine Learning Experience:</strong>Experience integrating AI/ML tools or agents into data workflows, or developing feature pipelines for machine learning models.</li><li>
<strong>Preferred Analytics Enablement:</strong>Experience designing self-service analytics platforms that enable business teams to access and use data efficiently.</li><li>
<strong>Preferred FinOps Expertise:</strong>Experience managing cloud data infrastructure costs and implementing cost optimization practices at scale.</li><h2>Benefits:</h2><li>
<strong>Mission-Driven Work:</strong>Contribute to a fintech initiative focused on expanding access to financial solutions for small and medium-sized businesses.</li><li>
<strong>Significant Technical Ownership:</strong>Shape the architecture, technical roadmap, tooling strategy, and operational performance of a business-critical data platform.</li><li>
<strong>Leadership Development:</strong>Progress from hands-on technical leadership into broader team management, including mentoring, performance development, and organizational planning.</li><li>
<strong>International Exposure:</strong>Help expand data infrastructure across Latin America and Europe while addressing complex multi-country architecture and regulatory challenges.</li><li>
<strong>Cross-Functional Collaboration:</strong>Work closely with experienced professionals across Data, Engineering, Product, Risk, Credit, Machine Learning, and Compliance.</li><li>
<strong>Innovative Technology Environment:</strong>Work with modern data technologies, cloud infrastructure, automation, and AI-enabled engineering tools.</li><li>
<strong>High-Growth Environment:</strong>Join a fast-paced organization where technical decisions can have a direct impact on business performance and long-term scalability.</li><li>
<strong>Ownership-Oriented Culture:</strong>Eligible team members may participate in a performance-based Phantom Share Program designed to align contributions with long-term business success and value creation.</li><li>
<strong>Professional Growth:</strong>Gain exposure to complex fintech challenges, embedded finance, credit underwriting, data governance, and international platform expansion.</li><li>
<strong>Remote Work:</strong>Work remotely from eligible locations in Latin America, including Brazil, Argentina, Colombia, and Chile.</li>