Data and Integration Engineer (AI and Automation)

About the role

We are seeking a skilled Data and Integration Engineer with a focus on AI and automation to support our internal service platform and broader MSP operating model. You will design, build, and maintain robust API integrations, automate recurring finance and operations processes, and contribute to a central data warehouse that powers reporting and dashboards.

Key responsibilities

• Design, develop, and maintain API integrations between systems such as Halo PSA, Float, HiBob, ApprovalMax, Xero and HubSpot, including two‑way synchronization and conflict handling.
• Implement error handling, alerting and reconciliation checks for all integrations.
• Automate manual finance and operations workflows, ensuring auditable, reproducible processes with scheduling and monitoring.
• Remediate data quality issues at source and establish controls to prevent recurrence.
• Contribute to the design and build of the central data warehouse, handling staging, entity matching, incremental loads and history.
• Collaborate with finance and operations teams to deliver reports and dashboards on top of the data layer.
• Develop AI‑assisted workflows that measurably improve throughput, using AI coding tools within a reviewed workflow.
• Gather requirements from non‑technical stakeholders and translate them into clear specifications.

Required profile

• Proactive, detail‑oriented and able to work independently.
• Strong communication skills to interact with finance, sales and operations colleagues.
• Experience working within a structured delivery process including planning, scope definition, peer review and documentation.

Required skills

• Hands‑on experience designing, building and supporting production API integrations.
• Knowledge of REST, OAuth2, webhooks and two‑way synchronization concepts (idempotency, retries, conflict resolution).
• Familiarity with Microsoft Graph, Entra APIs or comparable vendor APIs.
• SQL proficiency – queries, joins, views, stored procedures.
• Power Query (ETL, data transformation, M language).
• Automation of recurring processes with scheduling, monitoring and failure handling.
• Practical use of AI coding tools (e.g., Claude Code) within a reviewed workflow.