Senior Data Engineer (Microsoft Fabric)

Joblogic, established in 1998, is the UK’s leading Field Service Management (FSM) software platform with a global presence including offices in the UK, Pakistan, and Vietnam. Since a management buy-out in 2013, the company has grown from approximately £500K ARR to over £35M ARR, expanding its team from 11 to more than 500 employees. Recently, Joblogic secured a strategic growth investment exceeding £100 million from Vista Equity Partners, a global technology investor specializing in enterprise software. This investment is driving the company’s AI-first roadmap, expanding into Computer-Aided Facilities Management (CAFM), and supporting international growth across Europe and beyond. Joblogic’s platform serves over 100,000 users in industries such as HVAC, plumbing, electrical maintenance, facilities management, and building fabric maintenance, enabling businesses to streamline operations, improve profitability, ensure compliance, and embrace intelligent automation and predictive maintenance.

Key Responsibilities

- Own and maintain data ingestion pipelines supporting Marketing, Sales, Customer Success Management, and Finance, ensuring consistent and auditable data flow into the data lake.
- Design, build, and optimize ETL/ELT pipelines using Azure Data Factory; develop and tune complex SQL queries and stored procedures.
- Develop Python automation scripts and REST API integrations for external and third-party data sources.
- Enforce data quality, validation, and lineage across all pipelines to maintain data integrity.
- Collaborate closely with the Analytics team to deliver clean, modeled data for Power BI dashboards on schedule.
- Establish engineering best practices including Git workflows, code reviews, and CI/CD processes; mentor two data engineers.
- Monitor pipeline performance and costs, tuning compute and storage resources accordingly.
- Architect and implement an enterprise data warehouse/lakehouse from the ground up, including medallion architecture (bronze, silver, gold), dimensional models, canonical definitions, and a governed semantic layer.
- Lead the migration to Microsoft Fabric (OneLake, Lakehouse & Warehouse, Data Factory, Direct Lake for Power BI) or alternatively Databricks, managing strategy, phased cutover, and legacy system decommissioning.
- Define standards for data modeling, naming conventions, partitioning, indexing, and establish performance SLAs.
- Implement governance, security, data lineage, and cost controls to ensure scalable and sustainable platform growth.
- Own the technical roadmap and architectural direction for the data engineering function.

Required Qualifications

- Minimum 6 years of data engineering experience, including senior-level ownership of architecture and delivery on at least one end-to-end data warehouse or lakehouse build.
- Proven hands-on experience designing and implementing a data warehouse or lakehouse from scratch, with clear understanding of modeling decisions and trade-offs.
- Strong proficiency in Python for data engineering, automation, and API integration.
- Advanced SQL skills, including complex query writing, performance tuning, and stored procedures.
- Extensive experience with Azure Data Services, including Azure Data Factory, Azure SQL Database, Azure Storage (Blob/Data Lake), and Azure Functions.
- Solid foundation in ETL/ELT pipeline development, data modeling (dimensional/star schema), data transformation, validation, and quality assurance.
- Experience with REST API integration, Git/version control, performance optimization, and scalability.
- Strong problem-solving and debugging skills.

Preferred Qualifications and Benefits

- Hands-on experience with Microsoft Fabric components such as OneLake, Lakehouse & Warehouse, Data Factory pipelines/dataflows, and Direct Lake semantic models for Power BI is highly desirable.
- Experience leading migrations to Microsoft Fabric or Databricks is a strong advantage.
- Familiarity with Apache Spark, Databricks, Docker/containerization, CI/CD pipelines, Azure DevOps, Power BI semantic models, FastAPI/Flask, event-driven architectures (Service Bus, Kafka, RabbitMQ), monitoring and logging, data governance/security tools (e.g., Purview), cloud cost optimization, and testing methodologies (unit and integration) is beneficial.
- Proven leadership skills including mentoring, code review, and raising engineering standards.
- Excellent communication skills with the ability to translate technical concepts between business stakeholders, analytics, and engineering teams.
- Comfortable working with ambiguity, capable of setting standards and architecture from scratch while guiding the team forward.

This role offers the opportunity to lead and shape a critical function within a fast-growing SaaS company on a global scale, contributing directly to Joblogic’s ambitious growth plans and technological evolution.