At Kueski, we're dedicated to improving the financial lives of people in Mexico. Since 2012, we've been the leading buy now, pay later (BNPL) and online consumer credit platform in Latin America, known for our innovative financial services. Our flagship product, Kueski Pay, provides seamless payment solutions for both online and in-store transactions, establishing itself as the preferred option for nearly 30% of Mexico's top e-commerce merchants. Notably, we were the first to introduce BNPL on Amazon Mexico.
We're a tech company with a culture geared toward innovation, collaboration, and impact, fostering a strong, diverse, and inclusive workplace. Our commitment to excellence and ethical business practices has earned us multiple industry recognitions. In 2024, we were named one of the World’s Top FinTech Companies by CNBC and recognized as one of the most ethical companies in Mexico by AMITAI. Additionally, we were certified as a Best Place to Work for LGBTQ+ Equality by HRC Equidad MX 2025 and ranked among the Best Companies for Female Talent by EFY.
Over half of the Mexican population does not have access to financial products, due to the limitations of traditional banking institutions. Kueski’s mission is to provide financial opportunities to these people through technological innovation. As a Head of Data & Analytics Engineering, you will lead data initiatives, ensuring high-quality data ingestion, processing, and accessibility for decision-making and real-time insights. You will oversee ETL processes, maintain data integrity, and support key use cases like credit approval and fraud prevention. Additionally, you will empower cross-functional teams with analytics and reporting capabilities while fostering team growth and self-service data access.
As the leader of this organization, you are responsible for building and developing a world-class team of data engineers. You make sure the team delivers, and that their efforts always have exceptional quality, by setting up the right processes and quality assurance. This role is a technology leader with experience in building solutions for customers, experience in leading a team of engineers, and a track record of execution and delivery.
Key Responsibilities
Strategic Leadership: Define and execute the vision for data and analytics engineering, ensuring alignment with business goals and driving innovation in data architecture, infrastructure, and analytics capabilities.
Data Engineering Oversight: Lead efforts to grow and enrich the data lake with high-quality data, supporting decision-making, business performance monitoring, and reporting. Ensure batch and streaming ETL processes' integrity, quality, and continuity.
Scalable Data Infrastructure: Architect and manage real-time data processing environments for critical use cases, including credit approval, transaction processing, fraud detection and mitigation, alerts, and monitoring.
Analytics Engineering Enablement: Facilitate seamless access to high-quality, comprehensive data for cross-functional teams—including lending, credit risk, finance, fraud, compliance, and product—enabling efficient analytics, reporting, and strategic insights.
Advanced Analytics & Self-Service Capabilities: Support specialized analytics needs, including hypothesis testing, experimental design, and real-time reporting. Foster self-service capabilities, empowering teams to independently leverage data assets.
Talent Development & Team Growth: Build and mentor a team of data and analytics engineers, fostering a high-performance, customer-centric culture. Implement best practices for agile development, technical excellence, and continuous learning.
Cross-Functional Collaboration: Partner with product, engineering, and business stakeholders to align on data strategies, ensure data-driven decision-making, and optimize data accessibility across teams.
Operational Excellence: Establish and enforce quality control, security, and governance best practices for data management. Continuously evaluate emerging technologies to enhance data infrastructure, scalability, and efficiency.
Position Requirements (Experience & Competencies)
Education & Experience: Bachelor’s or Master’s degree in Computer Science, Data Engineering, or a related technical field, or equivalent work experience. 15+ years of relevant engineering experience, including 5+ years in a leadership role. Proven track record of delivering scalable data solutions.
Specialization in Data Systems & Processing: Expertise in data processing, management, and systems design. Strong understanding of data modeling for reporting, analytics, and real-time decision-making. Experience designing and testing data systems for large-scale, high-velocity environments.
Technical Expertise: Hands-on experience with modern data stacks for ingestion, storage, computation, and reporting, including Databricks, Spark, Kafka, OpenSearch, DBT, Tableau, or Preset. Deep knowledge of AWS cloud-based services (e.g., S3, EC2, EMR) and Big Data technologies.
Leadership & Collaboration: Ability to lead interdisciplinary teams through influence, driving impactful outcomes. Comfortable working cross-functionally with finance, risk, compliance, engineering, and product teams.
Strategic & Execution Excellence: Proven ability to translate complex business requirements into technical priorities and scopes. Strong execution skills, delivering high-quality solutions while meeting deadlines and business commitments.
Innovation & Problem-Solving: Quick learner with the ability to adapt to new technical and business domains. Passion for continuous learning, evaluating emerging technologies, and optimizing data infrastructure for performance and scalability.
Communication & Stakeholder Management: Excellent verbal, written, and presentation skills, with the ability to communicate architectural concepts to both technical and non-technical audiences.
At Kueski we embrace diversity in all forms, systematically promote equity, and ensure everyone feels included with a sense of belonging. We are committed to the full inclusion of all qualified candidates. As part of this commitment, we will make efforts to ensure reasonable accommodations are made during the hiring process. If reasonable accommodation is needed, please let the Talent Acquisition team know.
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