• Deliver data solution architecture for clients (data lakes, cloud data warehouses, data enhancement via machine learning APIs) • Be part of a team on larger scale deployment and deployments • Lead in the development and implementations of the company’s data engineering solutions on Azure • Undertake hands-on development for client projects • Provide guidance and demonstrate best practices when delivering solutions • Understand and utilise modern data platforms (cloud or on-premises) • Create and design compelling architectural blueprints to deliver value to our clients • Implement data engineering and machine learning solutions on the Azure technology stack • Identify and propose development and architectural improvements to existing systems • Participate in planning meetings as required

• Become a trusted advisor working together with our clients • Work independently as part of a small team to solve complex data engineering use-cases across a variety of industries • Design and develop the analytical layer, building cloud data warehouses, data lakes, ETL/ELT pipelines, and orchestration jobs • Work with modern tools such as Snowflake, Databricks, Fivetran, and dbt and credentialize your skills with certifications • Write code in SQL, Python, and Spark, and use software engineering best-practices such as Git and CI/CD • Support the deployment of data science and ML projects into production

• 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