Senior Engineer, Data Engineering

3 weeks ago


Glasgow, United Kingdom Head Resourcing Full time

Senior Data Engineer - Azure & Databricks Lakehouse Glasgow (3/4 days onsite) | Exclusive Role with a Leading UK Consumer Business

No sponsorship/ relocation provided sadly

Our incredibly successful client, consumer brand is undertaking a major data modernisation programme-moving away from legacy systems, manual Excel reporting and fragmented data sources into a fully automated Azure Enterprise Landing Zone + Databricks Lakehouse .
They are building a modern data platform from the ground up using Lakeflow Declarative Pipelines , Unity Catalog , and Azure Data Factory , and this role sits right at the heart of that transformation.
This is a rare opportunity to join early, influence architecture, and help define engineering standards, pipelines, curated layers and best practices that will support Operations, Finance, Sales, Logistics and Customer Care.
Engineer scalable ELT pipelines using Lakeflow Declarative Pipelines , PySpark , and Spark SQL across a full Medallion Architecture (Bronze - Silver - Gold) .
Implement ingestion patterns for files, APIs, SaaS platforms (e.g. subscription billing), SQL sources, SharePoint and SFTP using ADF + metadata-driven frameworks .
Apply Lakeflow expectations for data quality, schema validation and operational reliability.
Curated Data Layers & Modelling
Deliver star schemas, harmonisation logic, SCDs and business marts to power high-performance Power BI datasets .
Design and optimise orchestration using Lakeflow Workflows and Azure Data Factory .
Implement monitoring, alerting, SLAs/SLIs, runbooks and cost-optimisation across the platform.
DevOps & Platform Engineering
Build CI/CD pipelines in Azure DevOps for notebooks, Lakeflow pipelines, SQL models and ADF artefacts.
Ensure secure, enterprise-grade platform operation across Dev Prod , using private endpoints, managed identities and Key Vault.
Work closely with BI/Analytics teams to deliver curated datasets powering dashboards across the organisation.
Influence architecture decisions and uplift engineering maturity within a growing data function.
Databricks : Lakeflow Declarative Pipelines, Workflows, Unity Catalog, SQL Warehouses
Azure : ADLS Gen2, Data Factory, Key Vault, vNets & Private Endpoints
Languages : PySpark, Spark SQL, Python, Git
DevOps : Azure DevOps Repos, Pipelines, CI/CD
Power BI, Fabric

Significant commercial experience of Data Engineering with years delivering production workloads on Azure + Databricks .
Strong PySpark/Spark SQL and distributed data processing expertise.
Comfort with Git, CI/CD, automated deployments and modern engineering standards.
Databricks Certified Data Engineer Associate



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