Data Engineer

We’re looking for an experienced, proactive Data Engineer to join UCS College Group as part of our Digital Development team.

This is a mid-level role suited to someone with strong practical SQL experience who enjoys working directly with data: extracting it, cleaning it, modelling it, validating it, and turning it into reliable datasets that the organisation can trust.

The immediate focus of the role is to strengthen how we structure, manage, and use data across the organisation. This is a hands-on role working directly with source systems, staging tables, SQL transformations, data quality rules, and curated semantic data models that support reporting, analytics, statutory returns, and operational decision-making.

You’ll work closely with reporting teams, software engineers, DevOps colleagues, and business stakeholders to understand analytical requirements and translate them into clean, governed, reusable data models. Your work will help ensure that data is accurate, consistent, timely, and genuinely useful across the College Group.

In addition to day-to-day delivery, you’ll help shape our broader Data Strategy and Digital Roadmap as we transition towards a lakehouse-supported medallion architecture, with a particular focus on developing trusted silver and gold-layer datasets.

You’ll work within a hybrid-cloud Azure environment, contributing to scalable data solutions that improve data quality, reduce manual work, and support evidence-based decision-making across the organisation.

This is not primarily a Power BI dashboard development role. Power BI experience is useful, but the core requirement is the ability to build robust, well-modelled, SQL-driven data layers that reporting and analytics tools can consume confidently.

What You’ll Be Doing

You’ll take responsibility for the design, development, optimisation, and support of SQL-based data processes and curated analytical data models.

This includes:

• Designing, building, and maintaining robust ETL/ELT processes using SQL and Microsoft data technologies
• Extracting data from internal and external source systems and transforming it into reliable, structured datasets
• Building and maintaining staging layers, holding tables, transformed silver-layer datasets, and curated gold-layer semantic models
• Writing, reviewing, and optimising SQL queries, stored procedures, views, and transformations
• Creating reporting-ready data structures that are accurate, reusable, and easy for reporting teams to consume
• Applying data quality rules, validation checks, deduplication logic, and reconciliation processes
• Modelling data to support real organisational questions around academic performance, operations, compliance, and strategic planning
• Designing fact and dimension-style structures where appropriate to support analytical reporting
• Improving performance, reliability, and maintainability of existing SQL processes
• Monitoring data flows, diagnosing issues, and resolving data pipeline or data quality problems
• Working with stakeholders to understand definitions, business rules, and reporting requirements
• Supporting datasets and reports by ensuring the underlying data models are clean, trusted, and fit for purpose
• Applying secure data practices including role-based access controls and appropriate handling of sensitive information
• Contributing to documentation, data definitions, standards and engineering best practices

What We’re Looking For

We’re looking for someone who is comfortable working hands-on with data and SQL every day.

You should be able to demonstrate experience with:

• Strong SQL development, including joins, aggregations, CTEs, window functions, views, and stored procedures
• Building and maintaining ETL/ELT processes
• Working with staging tables, transformation layers, and reporting-ready datasets
• Designing data models for reporting and analytics
• Translating business rules into reliable data transformations
• Investigating data quality issues and validating outputs against source systems
• Optimising SQL queries and improving data process performance
• Working with relational databases, ideally SQL Server and/or Azure SQL
• Communicating clearly with both technical colleagues and business stakeholders

Experience with dimensional modelling, star schemas, medallion architecture, or semantic gold-layer modelling would be highly valuable.

We build and operate primarily within the Microsoft ecosystem. You’ll work hands-on with technologies such as:

• SQL Server, both on-premises and Azure-hosted
• Azure Data Factory and/or Microsoft Fabric Data Factory
• Azure Storage, Blob Storage, and Data Lake technologies where applicable
• Power BI datasets and semantic models
• Microsoft cloud and hybrid-cloud data services

The Impact of the Role

This role is central to improving how the College Group uses data.

Your work will:

• Create trusted, reusable datasets for reporting and analysis
• Enable accurate and timely statutory, operational, and performance reporting
• Reduce manual data handling and spreadsheet dependency
• Improve confidence in data quality, consistency and governance
• Support the transition towards a structured medallion-style data architecture
• Strengthen the organisation’s ability to make evidence-based decisions
• Improve automation, reliability and transparency across core data processes

Growth & Development

As a Data Engineer, you’ll be encouraged to:

• Take ownership of important data processes and analytical data models
• Contribute to architectural discussions and roadmap planning
• Help shape our Data Strategy and approach to silver and gold-layer modelling
• Propose improvements to data tooling, standards and engineering practices
• Develop deeper expertise in Azure data services and Microsoft Fabric
• Mentor junior colleagues where appropriate
• Work towards relevant Microsoft data engineering certifications

You’ll have autonomy, ownership, and the opportunity to make a real impact on how data engineering evolves within the organisation, while being supported by an experienced technical team.