System Engineer - L2 - Data and Integration

This role owns the integration capability that connects the service, commercial and operational systems. The priority is strong API integration engineering: understanding how to assess vendor APIs, design secure and supportable interfaces, automate end-to-end processes and operate integrations reliably in a live MSP environment.  

Experience with specific named platforms is useful, but the ability to integrate unfamiliar systems and tooling is more important. 

Microsoft Fabric will support the governed data and analytics layer, while Microsoft Foundry will support the development and operation of approved AI models and agents. The role will establish secure integration patterns across this architecture without being limited to these platforms or the tools currently in use. 

This is a hands-on engineering role supporting the internal service platform and wider MSP operating model. Success will be measured by reliable integrations, trusted data, reduced manual effort and solutions that are documented, monitored and supportable by the wider team. It has a clear data, automation and AI direction, but it is not an AI advisory or strategy position. ​

Key Responsibilities 

• Build and maintain API integrations between organization business systems. Immediate scope includes Halo PSA to Float two-way sync, HiBob to Float, and ApprovalMax into the central data layer. 
  

• Build integrations that report their own failures. Error handling, alerting and reconciliation checks, so that a broken or partial feed is flagged straight away rather than found weeks later in a report. 
  

• Automate recurring manual processes across finance and operations, including scheduled extracts, reconciliation support and supplier billing, to an auditable and reproducible standard. 
  

• Remediate data quality at source, starting with Halo PSA, Xero and HubSpot, including entity matching between Halo customers, Xero contacts and HubSpot records, and put controls in place so that issues do not recur. 
  

• Contribute to the design and build of the central data warehouse, including staging layer design, entity matching, incremental loading and history handling. 
  

• Work with colleagues across finance and operations to produce the reports and dashboards that sit on top of the data layer. 
  

• Build AI-assisted workflows where they measurably improve throughput, and use AI development tooling to accelerate build work. 
  

• Gather requirements directly from non-technical colleagues across finance, sales and operations, and convert them into written specifications. 
  

• Work within the established delivery process covering high level plan, scope of work, pre-sales authorisation, peer review and documentation before go-live. 
  

Essential Requirements: 

Integration and API engineering  

• Substantial hands-on experience designing, building and supporting API integrations between business systems in production. This core capability is more important than prior experience with any one platform in organization current stack.  
  

• Working knowledge of REST, OAuth2 and webhooks.  
  

• Two-way synchronisation, and a clear understanding of what makes it difficult: write conflicts, retries, idempotency and reconciling the two sides when they drift.  
  

• Experience integrating through Microsoft Graph, Entra APIs or comparable vendor APIs, with the ability to assess and adopt new interfaces as the MSP toolset changes.  
  

• Handling real production constraints, including permission limits, rate limits, schema access refused by a vendor, and endpoints that behave differently from their documentation.  
  

Data, automation and AI tooling  

• SQL proficiency: queries, joins, views and stored procedures.  
  

• Power Query: ETL, data transformation and M language.  
  

• Automating recurring processes end to end, including scheduling, monitoring and failure handling.  
  

• Practical use of AI coding tools such as Claude Code inside a reviewed workflow, with a clear account of how output is verified before it is relied on.  
  

Reporting and dashboards  

• Experience building and delivering reports and dashboards for business users, in any data visualisation tool. 
  

• Able to take a reporting requirement from a non-technical colleague through to a working, documented output.  
  

• Understanding of how the data model underneath a report determines what the report can and cannot do.  
  

Accuracy and reconciliation  

• You tie output back to source and present the reconciliation as part of delivery, unprompted.  
  

• You treat a figure that drives an invoice as materially different from a figure on a dashboard, and test it accordingly. 
  

• You surface the limitations of your own build before anyone else finds them.  
  

Professional skills  

• Strong analytical and problem-solving ability.  
  

• Excellent communication. You can explain technical concepts to finance professionals and business concepts to technical colleagues.  
  

• Self-starter, able to work independently with direction from the Finance Director.  
  

• Able to gather requirements from business stakeholders unaided, and patient with colleagues who do not think in data terms. Most of the people you will work with are accountants and engineers, not analysts.  
  

• Willing to say when something cannot be done safely, rather than building it anyway.  
  

• Disciplined working practice: work held in shared workspaces and source control rather than locally and documented so that a colleague could pick it up. 
  

Desirable skills  ​

• Azure AI Foundry: Experience orchestrating AI services over a data platform, with an understanding of Foundry as a control plane sitting above the data layer, and how models and APIs are selected and governed within it. 
  

• Microsoft Fabric: Experience with Lakehouse, pipelines, and a working understanding of capacity and licensing costs. Able to contribute to platform decisions such as Fabric vs Azure SQL based on cost, capacity and licensing considerations. 
  

• Data Warehouse & Architecture: Experience delivering a data warehouse or lakehouse, including staging layer design, dimensional modelling, incremental loading and slowly changing dimensions. 
  

• Data Governance: Working knowledge of sensitivity labelling, Purview, access control and data classification, sufficient to build within governance requirements set by others. 
  

• Accounting Platform Integration: Experience integrating Xero, QuickBooks, Sage or NetSuite with reporting tools or downstream systems. 
  

• PSA & MSP Tooling: Experience with Halo PSA, ConnectWise, Autotask or Datto, or comparable time-tracking and project management systems. Exposure to IT Glue, Liongard and Scalepad would be useful. 
  

• Sector Background: Experience within an MSP, professional services or another project-based business where billable utilisation and project margin are important. 
  

• Low-Code Automation: Experience with Power Automate, Zapier or similar tools, with the judgement to determine when a low-code approach is more appropriate than a coded solution. ​