The Opportunity
Nigel Wright Group has partnered with a well-established organisation to recruit an experienced Data Engineer to join its growing Business Intelligence function.
This is an excellent opportunity for a Data Engineer to take ownership of the design, development and maintenance of modern data infrastructure. Working within the Data Engineering team and reporting to the BI Manager, you will help transform raw information into trusted, accessible datasets that support reporting, analytics and business decision-making.
The role offers a high level of autonomy and the opportunity to work across Azure Data Factory, Snowflake, Microsoft Fabric and Power BI. You will contribute across the full data lifecycle, from pipeline development and data modelling through to orchestration, governance and the creation of reliable datasets and KPIs.
Whether you are an established Data Engineer or an experienced BI or SQL professional looking to develop further within data engineering, this position provides the opportunity to work with a modern technology stack while having a visible impact across the wider organisation.
The Role
Reporting into the BI Manager, you will design, build and maintain data solutions that enable accurate reporting, efficient workflows and meaningful business insight.
Key responsibilities include:
- Building, testing and maintaining data pipelines using Azure Data Factory and Snowflake
- Moving data from multiple source systems into the data warehouse and wider reporting environment
- Designing and maintaining data models across Snowflake and Microsoft Fabric
- Using medallion architecture to transform raw data into organised, accessible and curated datasets
- Applying data warehousing principles to effectively move, store and model information
- Creating cohesive datasets, measures and KPIs that provide a reliable single source of truth
- Working with operational and analytical teams to understand reporting requirements and structure data appropriately
- Improving data quality, governance, query performance and overall platform efficiency
- Documenting processes, introducing best practice and supporting business continuity
- Collaborating with colleagues across the BI team and wider organisation to troubleshoot issues and improve data workflows
About You
You will be a technically capable and commercially aware data professional who can work independently, manage competing priorities and translate business requirements into practical data solutions.
Key requirements:
- Strong experience of ETL and ELT processes
- Proficiency in SQL, including DDL and DML within a data warehouse environment
- Experience of data modelling, ideally including dimensional or Kimball modelling
- Understanding of data warehousing concepts and best practice
- Experience of query optimisation and performance tuning
- Good knowledge of data quality and governance principles
- Experience of Power BI, including DAX and Power Query
- Ability to communicate technical concepts clearly to non-technical stakeholders
- Strong problem-solving, critical-thinking and organisational skills
- A proactive approach to documentation, process improvement and knowledge sharing
The specification also identifies experience or knowledge of Azure Data Factory, Snowflake, Microsoft Fabric, Power Apps, Power Automate, Jira, Confluence and GitHub as relevant to the position. Python would be beneficial but is not essential, and candidates are not expected to demonstrate every technology listed.
Salary / Working Pattern
- Salary of £35,000 - £45,000
- Hybrid working - 1 day a week in Liverpool City Centre office & monthly team building sessions
- High-autonomy role with genuine ownership of data engineering activity
- Opportunity to work with Azure Data Factory, Snowflake, Microsoft Fabric and Power BI
- Broad exposure across pipelines, modelling, warehousing, orchestration and reporting
- Scope to simplify processes, introduce automation and shape data engineering best practice
- Collaborative position working with technical and non-technical stakeholders across the organisation
- Opportunity to create trusted data products that directly support operational and strategic decision-making
