Senior Data Engineer

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 and expanded 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 sectors 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.

We are seeking a Senior Data Engineer to join our expanding data team. This role requires a hands-on leader who can maintain and optimize existing Azure-based data ingestion and transformation pipelines while architecting and implementing a new enterprise data warehouse/lakehouse. You will lead the migration to Microsoft Fabric or Databricks, set engineering standards, and mentor junior engineers. This position offers the opportunity to build a data platform from the ground up with a focus on governance, semantic clarity, and scalability.

Key Responsibilities

- Own and maintain ingestion pipelines feeding Marketing, Sales, Customer Success, and Finance data into the data lake, ensuring consistent and auditable data flow.
- Design, build, and optimize ETL/ELT pipelines using Azure Data Factory, writing and tuning 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.
- Collaborate with the Analytics team to deliver clean, modeled data for Power BI reporting on schedule.
- Establish and uphold engineering best practices including Git version control, code reviews, and CI/CD processes.
- Monitor pipeline performance and costs, tuning compute and storage resources accordingly.
- Architect and implement an enterprise data warehouse/lakehouse with medallion architecture (bronze/silver/gold), dimensional models, canonical definitions, and a governed semantic layer.
- Lead the phased migration to Microsoft Fabric (OneLake, Lakehouse & Warehouse, Data Factory, Direct Lake for Power BI) or Databricks, including strategy, cutover, and legacy system decommissioning.
- Define standards for data modeling, naming conventions, partitioning, indexing, and performance SLAs.
- Implement governance, security, lineage, and cost controls to ensure scalable platform growth.
- Own the technical roadmap and architectural direction for the data engineering function.
- Provide technical leadership, mentoring two data engineers, and raising team standards.

Required Qualifications

- Minimum 6 years of experience in data engineering with senior ownership of at least one end-to-end data warehouse or lakehouse build from scratch.
- Proven ability to architect data warehouses, including modeling decisions, trade-offs, and outcomes.
- Strong proficiency in Python for data engineering, automation, and API integration.
- Advanced SQL skills including complex queries, performance tuning, and stored procedures.
- Extensive experience with Azure Data Services: 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, quality, and database management.
- Experience integrating REST APIs and using Git/version control systems.
- Strong skills in performance optimization, scalability, problem-solving, and debugging.

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, logging, data governance/security tools (e.g., Purview), cloud cost optimization, and Agile/Scrum methodologies is beneficial.
- Strong leadership skills with the ability to communicate effectively across business, analytics, and engineering teams.
- Comfortable working with ambiguity and capable of setting standards and architecture from a blank slate while guiding others.

This role offers the chance to be a key player in scaling a global SaaS business and shaping the future of its data platform as Joblogic accelerates toward £100M ARR internationally.