• Works as a positive team member of a project that may consist of Business Analysts, Project Managers, Information Architects, Data Analysts, and/or Database Administrators to deliver quality applications and components within scope, on time, within budget, and ensures compliance. • Manages workload effectively and report status of tasks in a timely manner. • Is able to guide stakeholders on solutions and support structure. • Ensures proper governance of prioritizing work from partners. • Forms tactical strategies to support multiple clients. • Leads and proactively identifies emerging technologies; develops proof-of-concepts, and promotes the usage of these emerging technologies. • Leads small to medium size technical teams, and mentors other analysts on regulation adherence. • Follows standard operational procedures and HIPAA regulations. • Develops strategies for managing complex data sets through maintaining data standards and metadata. • Applies biomedical informatics technical standards, methodologies, and principles to research-specific program needs, objectives, and outcomes. • Develops reporting infrastructure to meet multiple client needs. • Generates standard templates for architecture documentation related to current and proposed informatic solutions. • Performs other related duties as required.

• Work closely with Product and Development teams to help deliver components of the data roadmap • Gain a strong understanding of the organisation’s data needs and contribute to building accessible, reliable data solutions • Develop an interest across key business areas such as customer acquisition, conversion, retention, commercial performance, and user experience • Build, refine, and deliver data backlog items in collaboration with the Agile development team • Design, build, and maintain data pipelines, integrations, and transformations to support business reporting and analytics • Support data analysis, dashboard development, and self-service analytics by providing clean, well-structured datasets • Implement data management best practices to ensure data quality, consistency, and reliability • Apply techniques for accurate and complete data collection and validation • Follow secure and efficient procedures for data handling, storage, and processing • Assist colleagues with data access, extracts, and reporting as required • Monitor data systems and pipelines to identify issues, performance bottlenecks, and opportunities for improvement • Troubleshoot data-related issues and support routine maintenance and enhancements • Help ensure data platforms and databases are protected from data loss and security risks • Analyse data trends and provide well-structured datasets to support informed decision-making

• 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