• Architect end-to-end solutions to gather product telemetry, including offline data collection. • Evolve and maintain our telemetry stack with a strong focus on cost efficiency and scalability. • Define and implement best practices for product telemetry tracking, including standards, tests, and data plans, with a focus on quality and consistency. • Own and manage our data stacks, ensuring they scale with product and organizational needs. • Build and maintain data pipelines that connect business metrics with product metrics to empower product teams. • Support engineering teams by investigating data consistency issues and debugging complex SQL queries. • Share knowledge and mentor engineers on data architecture, tooling, and best practices. • Collaborate closely with the Director of Engineering to establish the data roadmap and translate stakeholder needs into clear action items.

• Design, build, and maintain a cloud-based data platform that supports analytics, MI, and insight for internal and external stakeholders • Lead the development and optimisation of data pipelines, ensuring they are scalable, reliable, and performant • Own and evolve data models, enabling consistent and trusted reporting across the business • Implement and improve data quality controls, monitoring accuracy, completeness, and reliability • Collaborate closely with data analysts and business stakeholders to translate data requirements into technical solutions • Support the ongoing evolution of data ingestion and integration solutions as the platform scales • Contribute to technical decision-making and best practices across the data engineering function • Play a key role in the transition from Azure-based data services to Google BigQuery, helping shape future architecture

• Lead the design, development, and optimization of data platforms and advanced analytics applications. • Collaborate closely with engineering, product, operations, and customer success teams to define architectural direction. • Drive best practices and guide cross-functional efforts to build scalable, reliable, and high-performance data platforms. • Power advanced analytics, machine learning, and mission-critical business operations across the organization.

• Ingesta y orquestación de datos con Azure Data Factory (ADF). • Procesamiento de datos a gran escala con Databricks (Python, Scala, Sparks). • Automatización, CI/CD, Y control de versiones con Azure devOps. • Integración con Azure Service Bus. • Diseño de arquitectura cloud data (Azure). • Tareas de gobierno, calidad y seguridad del dato. • Resolución de incidencias, soporte Azure.