• Diseñar y desarrollar soluciones de datos alineadas con la visión de Arquitectura de Datos. • Crear y optimizar ETLs, ELTs y APIs para manejo eficiente de datos. • Implementar estrategias de testing para validar calidad funcional y no funcional. • Proponer mejoras continuas en procesos y productos de datos. • Resolver incidencias técnicas y documentar soluciones conforme a estándares. • Mentorizar y apoyar el onboarding de nuevos integrantes del equipo.

• Design, build, and optimize end-to-end ETL pipelines for legal data from multiple jurisdictions, including cleaning, transformation, chunking, validation, embedding, and ingestion into vector databases • Work extensively with XML-based legal data feeds: parse, validate, normalize, and transform XML structures into scalable internal schemas and unified document formats • Develop and maintain data models and storage schemas that support continuously updated datasets while ensuring consistency, scalability, and accuracy across diverse datasets and large amounts of data • Coordinate data handover and integration from multiple internal and external data providers, including official sources, APIs, and web scraping pipelines, ensuring reliable and timely updates • Implement and continuously refine metadata enrichment strategies to maximize searchability, ranking quality, and relevance of legal information in vector databases. • Build and maintain a high-performance search and retrieval infrastructure enabling agent-based systems to call search functions and retrieve the most relevant legal information efficiently • Collaborate with product, AI, and legal domain experts to deliver high-quality, reliable data solutions • Own the data integration of one jurisdiction end-to-end

• Design, document, and maintain Axiom's enterprise data model, ensuring coherence and consistency across disparate systems and platforms. • Establish and enforce data governance policies, data quality standards, and associated assurance mechanisms to ensure the reliability and integrity of organizational data assets. • In coordination with the VP, Enterprise Applications, define and maintain the data architecture roadmap, including effort scoping, dependency identification, and alignment with enterprise technology strategy. • Directly manage the Data Engineer; provide technical mentorship, set priorities, and support professional development. • Serve as the primary data architecture liaison to the Product, Operations, and Data Science functions. • In coordination with the VP, Enterprise Applications, evaluate and determine the technology stack for AI solutions and other data initiatives. • Collaborate with the VP, Enterprise Applications and Integrations Lead to reconcile roadmap priorities and ensure integration-produced data meets enterprise data model standards. • Participate collaboratively in the design and implementation of Model Context Protocol integrations, enabling AI tooling to access Axiom's information assets. • Administer and govern the Databricks environment in coordination with the Data Engineer. • Establish and maintain data documentation standards: entity definitions, lineage, ownership, and access policies.

• Build and maintain ELT pipelines using Fivetran and custom API integrations via Dagster, including setting up new source connectors and troubleshooting. • Manage and improve Dagster orchestration — scheduling jobs, debugging failures, and keeping pipeline runtime tight. • Maintain and improve GitHub Actions CI/CD workflows to ensure safe, reliable deployment of dbt models into production. • Manage and maintain Snowflake infrastructure via Terraform — warehouses, roles, permissions, and resource monitors. • Write dbt models across staging, intermediate, and mart layers — clean, well-tested, and documented so the whole team can trust them. • Identify and address data quality issues before they become problems for the people depending on the data. • Handle ad-hoc analytics requests from stakeholders across the business — translate a business question into a query, turn a query into an insight. • Contribute to recurring deliverables: monthly growth reports, provider audits, forecasting documents, and ongoing Looker maintenance.