• Design, build, and maintain scalable and efficient cloud-based data pipelines. • Develop and support ETL/ELT processes for data integration and transformation. • Ensure compliance with information security and data governance standards. • Maintain and enhance cloud data environments, including data lakes and data warehouses. • Collaborate closely with engineering teams, product teams, and stakeholders. • Contribute to technical research, continuous improvement, and adoption of new technologies. • Maintain code quality using version control systems and CI/CD practices. • Support the strategic evolution of data engineering solutions and infrastructure.

• Support and maintain data ingestion pipelines, including connectors that pull data from NHS systems, practice management systems, and laboratory or equipment sources using APIs and screen-scraping. • Own and support the BigQuery ingestion layer and the downstream SQL Server and SQL Azure processing responsible for calculating dentist pay. • Proactively identify, investigate and resolve data ingestion issues while improving platform observability and monitoring. • Handle enterprise customer support requests and tactical enhancement requests for the existing platform. • Work across a highly distributed, brownfield, heavily customised environment supporting multiple bespoke customer deployments. • Review and occasionally adjust SQL-driven commands used by the legacy on-premises Delphi connector where required. • Contribute to tactical process improvements, including introducing source control through GitHub Enterprise and improving CI/CD practices using Azure DevOps. • Perform light-touch maintenance of the existing .NET web application. • Trace and resolve complex issues across stored procedures, Common Table Expressions (CTEs), SQL Server business logic and distributed systems. • Solve ambiguous production problems independently while collaborating within a Kanban team. • Help improve SDLC controls and engineering processes in an environment where production changes currently occur without CI/CD safeguards. • Deliver careful production changes while responding quickly to live customer issues.

• Build and optimize cloud-native data pipelines on AWS — ETL/ELT and the infrastructure underneath (Aurora, Redshift, dbt, Spark/EMR, Airflow, CDC) — using AI tooling as a standard part of the workflow. • Design and evolve the data models that power analytics, operational use cases, and AI/ML across thousands of studios. • Help raise the bar on data reliability — embed governance, testing, and lineage so both people and AI systems can trust the numbers by default. • Partner with product, and other engineering teams to turn ambiguous business problems into robust data solutions. • Evaluate and evolve new approaches with us — data mesh patterns, and emerging AI tooling — and help decide what genuinely earns a place in our stack. • Grow into our financial and regulatory reporting workstream (Finion Capital), where correctness and auditability matter most.

• Build and optimize cloud-native data pipelines on AWS — ETL/ELT and the infrastructure underneath (Aurora, Redshift, dbt, Spark/EMR, Airflow, CDC) — using AI tooling as a standard part of the workflow. • Design and evolve the data models that power analytics, operational use cases, and AI/ML across thousands of studios. • Help raise the bar on data reliability — embed governance, testing, and lineage so both people and AI systems can trust the numbers by default. • Partner with product, and other engineering teams to turn ambiguous business problems into robust data solutions. • Evaluate and evolve new approaches with us — data mesh patterns, and emerging AI tooling — and help decide what genuinely earns a place in our stack. • Grow into our financial and regulatory reporting workstream (Finion Capital), where correctness and auditability matter most.