Joblogic provides field service management software that connects office and field teams with scheduling, CRM, asset management, apps, vehicle tracking, invoicing, and BI reporting for skilled trades and facilities.
<div class="content-intro"><h3><strong>The Joblogic Story</strong></h3> <p>Established in 1998, <strong>Joblogic</strong> is the UK’s #1 <strong>Field Service Management</strong> (FSM) software platform. We are a global business with offices in the <strong>UK</strong>, <strong>Pakistan</strong>, and <strong>Vietnam</strong>. Since our management buy-out in 2013, we have grown from <strong>~£500K </strong>ARR to <strong>~£35M+ </strong>ARR and expanded our team from 11 to 500+ people.</p> <p>Recently, we secured a strategic growth investment from <strong>Vista Equity Partners </strong>— a global technology investor specialising in enterprise software. This investment includes over <strong>£100</strong> million in new primary capital and will fuel our next phase of growth by accelerating our <strong>AI-first roadmap</strong>, expanding our platform into CAFM (Computer-Aided Facilities Management) capabilities, and supporting our expansion across Europe and beyond.</p> <p>With <strong>Vista’s </strong>backing, we’re transforming from a successful UK business into a global scaling SaaS rocket ship, and we’d love for you to join us on our journey to <strong>£100M </strong>ARR across international markets.</p> <p><strong>Joblogic </strong>provides software to service contractors who install and maintain the built environment. Our platform helps businesses streamline operations, improve profitability, ensure compliance, and achieve rapid growth. With over <strong>100,000</strong> users across industries including HVAC, plumbing, electrical maintenance, facilities management, and building fabric maintenance, we are entering a new era of intelligent automation, predictive maintenance, and data-driven decision-making for service firms.</p></div><p></p> <section> <h2>About the role</h2> <p>We're scaling our data department and need a senior engineer who can do two things at once: keep the data that runs the business flowing reliably today, and architect the enterprise data warehouse that will run it tomorrow.</p> <p>In the near term you'll own and harden our current Azure-based ingestion and transformation pipelines. In the medium term — your biggest mandate — you'll design and implement our enterprise data warehouse / lakehouse from the ground up and lead the platform migration to Microsoft Fabric (our most likely direction) or Databricks.</p> <p>This is a hands-on and leadership role. You'll set engineering standards, mentor two data engineers, and be the technical owner of the engineering branch as the team and data volumes grow. If you've built a warehouse from a blank page and want to do it again — properly, with governance and a clean semantic foundation — this is that role.</p> </section> <section> <h2>The two mandates</h2> <div class="diptych"> <div class="mandate now"><strong><span class="tag">Now · run the business</span></strong> <h3>What you'll own today</h3> <ul class="list"> <li>Own and maintain the ingestion pipelines feeding Marketing, Sales, CSM and Finance into the data lake — consistent, auditable ingestion.</li> <li>Design, build and optimise ETL/ELT pipelines in Azure Data Factory; write and tune complex SQL and stored procedures.</li> <li>Build Python automation and REST API integrations for external and third-party data.</li> <li>Enforce data quality, validation and lineage across every pipeline.</li> <li>Partner with the Analytics team so clean, modelled data feeds Power BI on time.</li> <li>Set the engineering bar (Git, code review, CI/CD) and mentor the two engineers.</li> <li>Monitor pipeline performance and cost; tune compute and storage.</li> </ul> </div> <div class="mandate future"><strong><span class="tag">Next · build the platform</span></strong> <h3>What you'll build</h3> <ul class="list"> <li>Architect and implement the enterprise warehouse / lakehouse end-to-end — medallion (bronze / silver / gold), dimensional models, canonical definitions, governed semantic layer.</li> <li>Lead the migration to Microsoft Fabric — OneLake, Lakehouse & Warehouse, Data Factory, Direct Lake for Power BI (or Databricks): strategy, phased cutover, legacy decommission.</li> <li>Define modelling, naming, partitioning and indexing standards and performance SLAs.</li> <li>Put governance, security, lineage and cost controls in place so the platform scales without runaway spend.</li> <li>Own the technical roadmap and architecture direction for the engineering function.</li> </ul> </div> </div> </section> <section> <h2>Must-have — core skills & experience</h2> <div class="callout"> <div class="lbl"><strong>Non-negotiable</strong></div> <p>Proven, hands-on experience designing and implementing a data warehouse / lakehouse from scratch — not just maintaining one. You should be able to point to a warehouse you architected: the modelling decisions, the trade-offs, and the outcome.</p> </div> <ul class="checks"> <li>6+ years in data engineering, including senior ownership of architecture and delivery on at least one end-to-end warehouse/lakehouse build.</li> <li>Python — data engineering, automation and API work.</li> <li>SQL — complex queries, performance optimisation and stored procedures.</li> <li>Azure Data Services: <ul class="sub"> <li>Azure Data Factory (ADF)</li> <li>Azure SQL Database</li> <li>Azure Storage (Blob / Data Lake)</li> <li>Azure Functions</li> </ul> </li> <li>Data engineering fundamentals: <ul class="sub"> <li>ETL/ELT pipeline development</li> <li>Data modelling (incl. dimensional / star-schema)</li> <li>Data transformation</li> <li>Data validation & quality</li> </ul> </li> <li>Database design & management</li> <li>REST API integration</li> <li>Git / version control</li> <li>Performance optimisation & scalability</li> <li>Strong problem-solving & debugging</li> </ul> </section> <section> <h2>Target platform — Micr