• Liderar la investigación, validación y puesta en producción de modelos predictivos y de clasificación (regresión, clustering, inferencia causal, NLP). • Diseñar e implementar motores de decisión y sistemas de recomendación que soporten productos comerciales, de crédito y de experiencia del cliente en Tenpo. • Diseñar soluciones analíticas para mejorar el funnel de conversión de créditos, desde la prospección y originación hasta la retención. • Colaborar activamente con Marketing, Producto, Tecnología y Riesgo para traducir necesidades de negocio en soluciones de modelado concretas y asegurar su adopción efectiva. • Actuar como referente técnico del equipo de Data Science, revisando metodologías, validando implementaciones y contribuyendo al desarrollo de capacidades analíticas internas. • Mantener el 100% de los modelos en producción con documentación técnica completa y monitorear los tiempos de degradación dentro de los SLAs definidos.

Description We have an opportunity to impact your career and provide an adventure where you can push the limits of what's possible. As a Lead Software Engineer at JPMorganChase within the Corporate Technology team, you will design, develop, and deliver scalable, consumer-aligned data products that power executive reporting , analytics, AI and business applications. This role is ideal for an experienced software engineer who has a deep expertise in data development and is passionate about transforming complex enterprise data into trusted reusable products. The ideal candidate has extensive experience with Databricks, SQL, PySpark, Oracle and modern data engineering practices. They will partner with the business stake holders, analytics teams, UI developers, and product owners to build high quality data products that enable self-service analytics, dashboards, AI solutions, and operational reporting. Job Responsibilities - Design, develop, and maintain consumer-aligned data products that support enterprise reporting analytics - Develop curated datasets (Delta Lake tables) and analytics-ready models to support reporting, dashboards, and decision-making. - Drives team adoption of enterprise-authorized AI-assisted engineering practices within the work environment to improve code quality, delivery speed, and operational outcomes (e.g., AI-assisted code review/refactoring, test strategy acceleration, incident/root-cause analysis support), while establishing consistent validation standards (secure coding, peer review, automated testing) and promoting reuse of effective patterns across the team. - Applies knowledge of tools within the Software Development Life Cycle toolchain, including enterprise-authorized AI-assisted development and automation capabilities, to improve the value realized by automation. - Design efficient, maintainable SQL queries, views, stored procedures, and reusable data models - Build reusable data assets that support dashboards, AI use cases, automation, and business applications - Ensure data quality, governance, lineage, and documentation are incorporated into all solutions - Optimize data processing performance and identify opportunity to improve scalability and efficiency - Collaborate closely with frontend developers, analytics engineers, UX Designers and product owners - Stay current on emerging technologies and recommend improvements in cloud data architecture , AI, and automation Required Qualifications, Capabilities, and Skills - Formal training or certification on software engineering concepts and 5+ years applied experience - 8+ years in software engineering and/or data application development. - Expert-level SQL development experience, including query tuning and performance optimization. - Extensive experience with Databricks and the Databricks Lakehouse Platform. - Strong experience building data applications and pipelines using PySpark. - Experience with Oracle databases and enterprise data architecture / integration patterns. - Proven ability to design scalable, reusable data products for business consumers, grounded in strong data modeling (including dimensional modeling). - Experience with API integrations and consuming/combining data from multiple enterprise sources. - Operational excellence and modern delivery practices: incident response (triage/rollback/mitigation/postmortems), data lineage & impact analysis mindset, Agile methodologies, CI/CD, and strong analytical/communication/problem-solving skills. - Demonstrated experience leading effective use of approved AI-assisted software development tools (e.g., for coding, code review, test acceleration, troubleshooting) with the ability to set team expectations for validating AI outputs for correctness, performance, and security. - Strong understanding of responsible AI use in engineering workflows, including data sensitivity considerations, secure handling of inputs/outputs, and adherence to resiliency and security expectations; experience coaching engineers on safe, compliant adoption within delivery practices Preferred Qualifications, Capabilities, and Skills - Experience building executive dashboards using Tableau, Qlik, or Power BI. - Experience supporting AI, machine learning, or Generative AI initiatives. - Experience with automation technologies and workflow orchestration. - Experience designing semantic layers or enterprise data products. - Familiarity with cloud platforms such as AWS or Azure. - Experience mentoring engineers and leading technical solution design. About Us JPMorganChase, one of the oldest financial institutions, offers innovative financial solutions to millions of consumers, small businesses and many of the world’s most prominent corporate, institutional and government clients under the J.P. Morgan and Chase brands. Our history spans over 200 years and today we are a leader in investment banking, consumer and small business banking, commercial banking, financial transaction processing and asset management. We offer a competitive total rewards package including base salary determined based on the role, experience, skill set and location. Those in eligible roles may receive commission-based pay and/or discretionary incentive compensation, paid in the form of cash and/or forfeitable equity, awarded in recognition of individual achievements and contributions. We also offer a range of benefits and programs to meet employee needs, based on eligibility. These benefits include comprehensive health care coverage, on-site health and wellness centers, a retirement savings plan, backup childcare, tuition reimbursement, mental health support, financial coaching and more. Additional details about total compensation and benefits will be provided during the hiring process. We recognize that our people are our strength and the diverse talents they bring to our global workforce are directly linked to our success. We are an equal opportunity employer and place a high value on diversity and inclusion at our company. We do not discriminate on the basis of any protected attribute, including race, religion, color, national origin, gender, sexual orientation, gender identity, gender expression, age, marital or veteran status, pregnancy or disability, or any other basis protected under applicable law. We also make reasonable accommodations for applicants’ and employees’ religious practices and beliefs, as well as mental health or physical disability needs. Visit our FAQs for more information about requesting an accommodation. JPMorgan Chase & Co. is an Equal Opportunity Employer, including Disability/Veterans About the TeamOur professionals in our Corporate Functions cover a diverse range of areas from finance and risk to human resources and marketing. Our corporate teams are an essential part of our company, ensuring that we’re setting our businesses, clients, customers and employees up for success.

• Design, optimize, and scale cloud-based data platforms for business-critical applications. • Build robust data pipelines and ensure reliable, secure, and scalable data operations across AWS environments. • Collaborate with engineering teams to support production systems and improve data accessibility. • Implement automation for data-driven decision making at scale. • Review and optimize complex SQL queries to improve application performance. • Administer AWS database services and manage schema changes across environments. • Collaborate with Software Engineers to resolve data-related incidents.

• Build, test, and document dbt models (staging, intermediate, marts) aligned to Kimball dimensional modeling best practices. • Implement data quality checks (dbt tests, sources, freshness) and contribute to monitoring data reliability. • Collaborate with analytics, product, and domain stakeholders to translate business needs into well-modeled datasets. • Proactively audit, define, and standardize key business metrics in collaboration with stakeholders to ensure consistency and trust across reporting platforms. • Support source onboarding and ingestion from APIs, files, or databases into the warehouse. • Maintain clear documentation for datasets, lineage, and transformation logic. • Assist with CI/CD for analytics code (Git workflows, PR reviews, environments). • Optimize model performance (incremental strategies, partitions/clustering, query tuning). • Troubleshoot pipeline/data issues and contribute to root-cause analyses. • Proactively identify improvement opportunities and drive them to completion with high ownership.