Summary
✨ AI‑Generated
A technical BI development opportunity within a data-focused team. The role covers the full analytics lifecycle, including ingestion, transformation, modelling, pipeline enhancement, and dashboard delivery.
Highlights
Hands-on BI development role with ownership of data modernization, analytics delivery, and end-to-end reporting solutions.
Description
Full Stack BI Developer
Location: Peterborough, hybrid, up to 3 days per week onsite
Contract: 6-month Fixed Term Contract initially, with potential extension or permanent opportunity
Salary: £75,000 to £90,000 pro rata
Start: ASAP
Role Overview
We are looking for a hands-on Full Stack BI Developer to support a BI platform replacement and data modernisation project.
You will join an established Data & Analytics team, working alongside a Business Analyst, Data Analyst and Senior Data & Analytics Manager.
This is a technical delivery role covering the full Azure data and BI stack.
The project is already underway, with existing integrations and data pipelines in place.
You will take ownership of the existing solution, develop new datasets, enhance pipelines where required, and deliver reporting solutions through Power BI.
You will work across the full BI lifecycle, from understanding business requirements and source data through ingestion, transformation and data modelling to the development of Power BI reports and dashboards.
About the Project
This is a multi-phase programme focused on replacing an existing BI platform and developing new datasets within the Azure data environment.
The initial six-month FTC will support the delivery of phase one and progression into phase two.
There is potential for the position to be extended or develop into a permanent opportunity as the programme progresses.
As the foundations of the platform are already in place, we are looking for someone who can quickly understand existing pipelines, integrations and data structures, take ownership of the technical delivery, and continue developing the solution.
What you'll be doing
Develop and maintain end-to-end BI and data solutions across Azure, Databricks and Power BI.Work hands-on with Azure Data Factory pipelines, including developing new pipelines and modifying existing integrations where required.Develop Databricks notebooks using SQL and Python to transform and prepare data.Build and optimise datasets and data models for reporting and analytics.Develop dimensional and star-schema data models.Build Power BI semantic models, reports and dashboards using DAX.Pick up and enhance an existing data platform rather than starting from scratch.Integrate data from enterprise source systems.
The current environment includes JDE ERP and other operational data sources.Work closely with the Business Analyst and Data Analyst to translate business requirements into technical data and reporting solutions.Engage directly with business stakeholders to understand requirements, explain technical concepts and ensure solutions meet business needs.Troubleshoot and enhance existing BI solutions and data pipelines.Follow established data architecture, governance and development standards.Use appropriate version control and CI/CD practices to support controlled deployment.
Essential experience
Strong hands-on experience delivering end-to-end BI/data solutions.Azure Data Factory, including ETL/ELT pipeline development.Strong Databricks experience.Hands-on development of Databricks notebooks using SQL and/or Python.Advanced SQL.Power BI development, including semantic models, DAX, dashboards and reports.Data modelling, ideally dimensional/star-schema modelling.Experience working with existing enterprise data platforms and integrations.Ability to understand business requirements and translate them into working technical solutions.Strong stakeholder communication skills.
Desirable experience
JDE or similar ERP data experience.Databricks Lakehouse and Medallion Architecture.Delta Lake.Azure Data Lake and/or Synapse.Git and Azure DevOps.Data governance, quality, security and lineage.Experience working with finance, manufacturing, stock, supply chain or operational datasets.