Job Description

Job Advert


Liberty Wines is modernising its data estate: migrating from on-prem Analysis Services to the cloud, moving our WMS, ERP and bespoke apps to scalable platforms, and expanding AI/ML initiatives.


We are evaluating both Fabric and Databricks as a potential strategic fit. As our hands-on Data & Analytics Engineer, you'll play a key role in shaping and influencing that decision, helping assess the best platform for our needs based on your experience and contributing to successful delivery on either.


You will work end-to-end, from schema design to dashboard storytelling, and be the pivotal data voice in the Technology team. This role offers broad ownership across tooling, standards, engineering and enablement rather than being confined to a narrow BI silo.

Key Responsibilities

Data Platform Build-out

Design relational & Lakehouse schemas in Fabric or Databricks Lead the re-architecture of SSAS cubes to modern Lakehouse models Set up medallion architecture and govern data pipelines. Contribute to the evaluation and selection of data platform architecture based on performance, usability, and alignment with Liberty Wines' long-term data strategy

Data Engineering

Develop and orchestrate ETL / ELT, middleware and integrations Ingest data from WMS, ERP, ecommerce, IoT and ad-hoc sources (CSV, APIs, unstructured).

Analytics & Reporting

Model data (DAX, Tabular Editor) and build stunning dashboards used by Sales, Buying, Ops & Finance Optimise datasets for performance, incremental refresh and DirectQuery.

AI / ML Enablement

Work with Liberty's AI & Automation Dev Team to prepare and expose curated data to our AI/ML toolsets and workflows.

Stakeholder Enablement & Documentation

Maintain clear documentation for BI projects, processes, and solutions. Enforce data governance practices to ensure compliance with organizational standards. Upskill analysts through show-and-tell sessions and guard-rail documentation

Governance & DevOps

Implement CI/CD, source control (Git), and automate Fabric workspace deployment Define data-quality rules, lineage and catalogue standards

About You

Solid track record in Data Engineering, BI Development or Analytics Engineering roles Strong SQL skills and a solid understanding of data-modelling principles (e.g., dimensional modelling, 3NF) Experience designing and building modern data pipelines and Lakehouse architectures Hands-on experience with at least one enterprise-grade data platform (e.g., Microsoft Fabric, Azure Synapse, Databricks, or equivalent) Proficiency in ELT/ETL development using tools such as Data Factory, Dataflow Gen2, Databricks Workflows, or similar orchestration frameworks Experience with Python and/or PySpark for data transformation, automation, or pipeline development Familiarity with cloud services and deployment automation (e.g., Azure, AWS, Terraform, CI/CD, Git) Ability to deliver clear, insightful, and performant data visualisations and dashboards using tools such as Power BI, Databricks Dashboards, or other modern BI platforms Comfortable enabling self-service analytics and natural language querying tools (e.g., Power BI Q&A, Databricks Genie) Agile mindset: embraces iterative delivery, peer code reviews, and test-driven development Excellent stakeholder engagement and communication skills -- confident working cross-functionally and enabling others to use and trust the data

Desirable

:
Experience with Lakehouse patterns; setting standards, quality checks etc. Parquet partitioning and clustering to optimise for query speed and cost GitHub Actions REST APIs ML Ops tooling

What you can expect

25 days holiday excluding public holidays increasing after 2 years' service Participation in Company and Personal bonus schemes Company pension scheme matching up to 5% of contributions 18 weeks enhanced maternity leave and 4 weeks paternity leave. Cycle to work scheme & Season ticket loan Employee Assistance Programme Travel insurance Employee wine discount Retail, wellbeing, technology, and travel discounts * Plus many other Liberty Wine perks