Data and Integration Engineer

Job description

Data and Integration Engineer (AI and Automation) Job Overview Our client is a UK-based managed service provider delivering technology and operational services to customers in the Accountancy, Financial Services, and Asset Management sectors. They are looking for a hands-on Data and Integration Engineer (AI and Automation) to own and develop the integration capability connecting their service, commercial, financial, and operational systems. The role will focus on API integration engineering, data quality, automation, reporting, and the secure integration of AI capabilities. The successful candidate will be responsible for building reliable, well-documented, and supportable solutions that reduce manual effort and improve the quality and accessibility of business data. Job Details Work Setup: Work from Home Schedule: Monday to Friday | 8:00 AM to 5:00 PM | UK Time Holidays: Will follow UK holidays Responsibilities Build and maintain API integrations between business systems, including two-way synchronization between platforms and integration with the central data layer. Build integrations with appropriate error handling, alerting, and reconciliation checks to ensure broken or partial data feeds are identified promptly. Automate recurring manual processes across finance and operations, including scheduled extracts, reconciliation support, and supplier billing, using auditable and reproducible processes. Identify and remediate data quality issues at source, including entity matching across customer, accounting, and CRM records, and implement controls to prevent recurring issues. Contribute to the design and development of the central data warehouse, including staging layer design, entity matching, incremental loading, and history handling. Work with finance and operations stakeholders to develop reports and dashboards based on the central data layer. Build AI-assisted workflows where they can measurably improve business throughput and use AI development tools to accelerate engineering work. Gather requirements directly from non-technical stakeholders across finance, sales, and operations and translate business needs into clear written specifications. Assess vendor APIs and develop secure, reliable integration solutions for both existing and unfamiliar systems. Work with production constraints such as permissions, rate limits, limited schema access, and differences between vendor documentation and actual endpoint behaviour. Ensure solutions are documented, monitored, supportable, and maintained using disciplined development and source-control practices. Follow the established delivery process, including planning, scope definition, pre-sales authorization, peer review, documentation, and go-live activities. Qualifications Essential Qualifications Substantial hands-on experience designing, building, and supporting API integrations between business systems in a production environment . Strong working knowledge of REST, OAuth2, and webhooks . Experience with two-way synchronization, including understanding of write conflicts, retries, idempotency, and reconciliation. Experience working with Microsoft Graph, Entra APIs, or comparable vendor APIs . Ability to work with real-world production constraints, including permission limitations, rate limits, restricted schema access, and inconsistent API behaviour. Strong SQL skills, including queries, joins, views, and stored procedures. Experience with Power Query , including ETL, data transformation, and M language. Experience automating recurring processes end-to-end, including scheduling, monitoring, and failure handling. Practical experience using AI coding tools within a reviewed workflow, with the ability to verify and validate AI-generated output. Experience building and delivering reports and dashboards for business users using Power BI or a comparable reporting tool . Ability to translate reporting requirements from non-technical stakeholders into working and documented outputs. Understanding of how the underlying data model affects reporting capabilities and limitations. Strong focus on accuracy, reconciliation, and traceability of data back to its source. Strong analytical and problem-solving skills. Excellent communication skills, with the ability to explain technical concepts to finance professionals and business concepts to technical colleagues. Self-starter who can work independently with direction from the Finance Director. Ability to gather requirements directly from business stakeholders and work effectively with colleagues who may have limited data-related knowledge. Willingness to identify and communicate when a solution cannot be implemented safely. Strong documentation and working practices, including maintaining work in shared workspaces and source control. Preferred Qualifications Experience with Azure AI Foundry , particularly in orchestrating AI services over a data platform and understanding how models and APIs are selected and governed. Experience with Microsoft Fabric , including Lakehouse and pipelines, with an understanding of capacity and licensing costs. Experience delivering a data warehouse or lakehouse, including staging layer design, dimensional modelling, incremental loading, and slowly changing dimensions. Working knowledge of data governance concepts such as sensitivity labelling, Microsoft Purview, access control, and data classification. Experience integrating accounting platforms such as Xero, QuickBooks, Sage, or NetSuite with reporting tools or downstream systems. Experience with PSA/MSP platforms such as Halo PSA, ConnectWise, Autotask, or Datto. Exposure to IT Glue, Liongard, or Scalepad. Advanced Power BI skills, including DAX, semantic models, star schema design, and Power BI Service administration. Experience in an MSP, professional services, or project-based business where billable utilization and project margin are important. Experience with low-code automation tools such as Power Automate or Zapier , with the judgment to determine when low-code is more appropriate than custom development.