Senior Data Engineer

Flannery Plant Hire is one of the UK’s leading providers of operated and self‑drive plant hire services, supporting major infrastructure and construction projects nationwide. We’re investing in data to improve operational efficiency, sustainability, and customer experience.

We’re looking for a Senior Data Engineer who pairs solid engineering fundamentals with an analytical mindset. You’ll build reliable data foundations, enable high‑quality reporting and self‑serve analytics, and help us take our Power BI capability to the next level. We care more about attitude, work ethic, and proven delivery than formal qualifications.

• Design, build, and maintain scalable data pipelines and ELT/ETL processes across telematics, ERP, IoT, CRM, and finance systems.
• Model and deliver robust data products (lakehouse/warehouse, marts, semantic models) that power BI, analytics, and data science.
• Lead our use of Microsoft Fabric for ingestion, transformation, and analytics, including Lakehouse, Warehouse, Pipelines, Notebooks, Dataflows Gen2, and One Lake.
• Build and optimise Power BI datasets and semantic models (including Direct Lake and incremental refresh) in partnership with analysts.
• Implement data governance, quality, lineage, and security‑by‑design; drive documentation, testing, and version control standards.
• Tune performance across SQL, storage, and BI layers; manage cost and reliability in the cloud (Azure preferred).
• Enable streaming and near‑real‑time use cases where needed (e.g., telematics/IoT) using appropriate services.
• Champion modern Data Ops practices (CI/CD, environment management, automation) and mentor junior team members.
• Collaborate closely with stakeholders to translate business needs into well‑designed data solutions and clear metrics.

• Proven experience (5+ years) as a data engineer delivering production‑grade data solutions.
• Strong SQL and proficiency in at least one programming language (Python preferred; Scala/Java also valuable).
• Hands‑on experience building and operating ETL/ELT pipelines and data models (Kimball, Data Vault, or similar).
• Cloud data experience (Azure preferred), including storage, compute, and security fundamentals.
• Practical Power BI experience as a data engineer: shaping data models, optimising for performance, and collaborating with analysts.
• Solid grasp of data governance, privacy, and security best practices; comfortable with Git and documentation.
• Bias to action, ownership, and continuous improvement; capable of balancing speed with quality.

• Microsoft Fabric: creating and managing a Fabric Warehouse or Lakehouse (and underlying “database” objects), building Pipelines/Notebooks, using One Lake, and enabling Direct Lake for Power BI.
• Experience with telematics, IoT, logistics, or construction data.
• Streaming platforms and APIs (e.g., Kafka, Event Hubs) and batch orchestration.
• Data Ops/CI‑CD for data (Azure Dev Ops/Git Hub Actions), dbt, unit/integration testing for data.
• DAX fundamentals and Power BI performance tuning at scale.
• Formal qualifications or certifications (e.g., Azure DP‑203, Microsoft Fabric Analytics Engineer) are welcome but not required.

• Reliable, well‑documented pipelines feeding a governed lakehouse/warehouse.
• Faster, more trusted Power BI reporting backed by high‑quality semantic models.
• Clear data standards adopted across the team, with CI/CD and automated testing in place.
• Demonstrable cost, performance, and data quality improvements on key domains (e.g., telematics, operations, finance).
• Competitive salary and package.
• 24 days plus bank holiday annual leave, plus personal leave.
• Training and professional development tailored to you.
• Employee Assistance Programme.
• Strong safety and sustainability culture.
• Modern equipment and supportive, team‑oriented environment.

If you’re a hands‑on engineer who loves building practical, scalable data solutions and wants to grow an organisation’s Power BI and Microsoft Fabric capability, we’d like to hear from you.

Location:

London, England, United Kingdom