Data Engineer (Ref: 195541)

Our client stands as a prominent player within the products manufacturing sector, dedicated to innovation, quality, and sustainability. This organization is committed to delivering superior nourishment options worldwide, consistently striving to not just meet, but surpass industry benchmarks. Their mission is to ensure their customers has access to top-tier products.

The Data Engineer will design, build, and maintain scalable data pipelines and data models across the Azure data platform. The role is hands-on and engineering-focused, with responsibility for ETL/ELT processes, transformations, SQL development, and data modelling.

While the engineer should be comfortable supporting reporting and Power BI use cases, the primary focus is on back-end data engineering rather than analytics.

• Design, build, and orchestrate ETL/ELT pipelines using Azure Data Factory and Azure Fabric

• Develop and optimise SQL-based transformations and data models

• Implement data processing in Azure Databricks (PySpark / SQL notebooks, Delta Lake)

• Build and maintain data lake and data warehouse structures in Azure

• Ensure high data quality through validation, transformation, and monitoring

• Support integration across Azure Data Lake, Synapse, SQL pools, and BI layers

• Work closely with BI developers to enable reliable, well-modelled datasets for reporting

Platform & Engineering

• Develop pipelines with:

  • Linked Services

  • Triggers

  • Workflows

  • Orchestration logic

• Build semantic layers and dimensional models (star/snowflake)

• Optimise performance and scalability across data assets

• Contribute to standards for data engineering, modelling, and platform design

Documentation & Governance

• Maintain documentation of pipelines, models, and data flows

• Support data governance, security, and quality initiatives

• Strong Data Engineering background (not architecture-only)

• Advanced SQL (modelling, optimisation, stored procedures)

• Azure Data Factory – building & orchestrating pipelines

• Azure Databricks – PySpark / SQL notebooks, Delta Lake

• Azure Data Lake Storage

• Azure Synapse Analytics – SQL pools, serverless SQL, pipeline integration

• Azure Fabric

• Programming: Python, Advanced SQL

Data Modelling

• Star & snowflake schemas

• Normalisation

• Slowly Changing Dimensions (SCDs)

• Semantic layer design