• Diseñar y construir pipelines de datos: Diseñar, construir y mantener pipelines para la ingestión, limpieza, transformación y carga (ETL/ELT) de datos desde múltiples fuentes hacia almacenes de datos y plataformas analíticas. • Administración de la infraestructura y almacenamiento de datos: Configurar y administrar bases de datos, sistemas de almacenamiento y herramientas de procesamiento. • Optimización de rendimiento y eficiencia: Identificar y resolver cuellos de botella en pipelines y sistemas de almacenamiento. • Gestión de metadatos y documentación: Desarrollar y mantener mecanismos de catalogación y documentación para conjuntos de datos, pipelines y procesos de transformación. • Seguridad, control y cumplimiento de datos: Implementar medidas de seguridad y cumplimiento para proteger la confidencialidad, integridad y disponibilidad de la información. • Colaboración e integración con equipos y productos: Trabajar de forma articulada con equipos de ciencia de datos, producto, ingeniería de software y operaciones. • Entendimiento del negocio para orientar el uso del dato: Profundizar en el conocimiento del negocio y del sector.

• Data Engineer will work closely with the rest of the product team and business peers to effectively execute Data project initiatives. • Deliver in a fast-paced and deadline-driven environment. • Responsible for maintenance of the data applications and expected to automate processes with no or minimal human intervention. • Development and maintenance of ELT snowflake data warehouse solutions. • Collaborate with internal and external technology and business partners to implement product changes. • Produce detail design and unit test documents, as required. • Critically analyze business requirements, architect and implement Data solutions. • Define, develop and maintain standards and processes to ensure effective ETL solution Production maintenance. • Work closely with product manager to develop and execute action plans to address gaps. • Recommend innovations that enhance and/or provide a competitive advantage to the organization. • Communicate effectively with both the business and technical teams. • Mentor junior offshore developers to accomplish results. • Build and continuously improve data engineering best practices.

• Build data applications and processes using Python, SQL, and Django; manage and query data in PostgreSQL, Oracle, and cloud-native databases • Examine, extract, cleanse, and load data while implementing quality assurance rules and tools to ensure consistent and accurate data • Work with healthcare-specific data processes such as EDI file transfers, claims adjudication, audits, eligibility verification, and reporting workflows • Collaborate with cross-functional teams (Data Analysts, Data Scientists, Product, Reporting, Account Management) to define requirements and deliver data-driven solutions • Ensure data quality, integrity, and security through automated validation, auditing, and monitoring, with compliance to HIPAA and CMS regulations • Monitor, maintain, and tune pipeline performance; proactively troubleshoot and resolve complex data flow and system issues • Provide technical mentorship to Data Engineers, sharing expertise in data modeling, pipeline development, and troubleshooting practices • Research and propose improvements to the tech stack and data engineering processes • Participate in sprint planning, refinement, and estimation to support implementation awareness and delivery

• Analyse and ingest new datasets from varied sources • Design, build, and support cloud infrastructure • Design, build, and support AI and ML processes and infrastructure • Design and build modern, metadata driven data pipelines and data streams • Design and build data service APIs • Transform and cleanse complex datasets • Analyse current business practices, processes and procedures • Implement effective metrics and monitoring processes