• 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.

Role Description We're partnering with a growing organisation looking to expand its data team with the addition of a Senior Data Engineer. This is an opportunity to work on a range of data projects, helping to build and optimise modern data solutions that support reporting, analytics, and business decision-making. You'll work closely with both technical and non-technical stakeholders, contributing to the development of scalable data platforms and pipelines while supporting the ongoing evolution of the organisation's data capabilities. - Develop and maintain data pipelines and integration solutions - Support the design and enhancement of cloud-based data platforms - Work with stakeholders to understand and deliver data requirements - Improve data quality, reliability, and performance - Contribute to data architecture and best practice initiatives - Support the delivery of data-driven projects across the business Qualifications - Experience working as a Data Engineer or in a similar data-focused role - Strong SQL and Python skills - Experience building and maintaining data pipelines - Exposure to cloud technologies such as AWS, Azure, or GCP - Understanding of data warehousing - Strong problem-solving and stakeholder engagement skills - Commercial experience working with modern data platforms Benefits - Fully remote working - Competitive salary and benefits package - Exposure to modern technologies and data projects - Flexible working - Opportunities for professional development and progression Company Description