Data and Integration Engineer (AI & Automation)

About the role

Our client is a UK‑based managed service provider delivering technology and operational services to the accountancy, financial services and asset management sectors. They are seeking a hands‑on Data and Integration Engineer (AI and Automation) to own and develop the integration capability that connects their service, commercial, financial and operational systems.

Key responsibilities

• Design, build and maintain API integrations between business systems, including two‑way synchronization and integration with a central data layer.
• Implement error handling, alerting and reconciliation checks to quickly identify broken or partial data feeds.
• Automate recurring manual finance and operations processes such as scheduled extracts, reconciliation support and supplier billing.
• Identify and remediate data‑quality issues at source, applying entity‑matching controls across customer, accounting and CRM records.
• Contribute to the design and development of a central data warehouse, including staging layer design, incremental loading and history handling.
• Develop reports and dashboards for finance and operations stakeholders using the central data layer.
• Build AI‑assisted workflows that measurably improve business throughput and use AI development tools to accelerate engineering work.

Required profile

• Substantial hands‑on experience designing, building and supporting production‑grade API integrations.
• Strong working knowledge of REST, OAuth2, webhooks and two‑way synchronization concepts such as idempotency and retries.
• Proficiency with Microsoft Graph, Entra APIs or comparable vendor APIs.
• Advanced SQL skills, including queries, joins, views and stored procedures.
• Experience with Power Query (ETL, data transformation, M language) and Power BI report development.
• Practical experience using AI coding tools within a reviewed workflow and validating AI‑generated output.

Required skills

• REST, OAuth2, webhooks
• Microsoft Graph, Entra APIs
• SQL
• Power Query (M language)
• Power BI (including DAX)
• Azure AI Foundry (or similar AI orchestration)
• Microsoft Fabric (Lakehouse, pipelines)
• Power Automate or Zapier for low‑code automation