BI Lead: Azure, Fabric & Power BI Strategy

DB Recruitment

Maynooth

On-site

EUR 90,000 - 140,000

Full time

34 hours ago
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Job summary

DB Recruitment is seeking an experienced leader to drive our data analytics and BI initiatives in Ireland. You will mentor a growing analytics team, partner with senior leadership to translate business needs into scalable solutions, and oversee the deployment of Fabric and Power BI across business units in collaboration with our implementation partner.

The role requires hands-on design and development of data warehouses, ETL pipelines, and data cubes, plus stewardship of master data within the

Qualifications

  • Minimum 5 years of experience in data analytics and BI development.
  • Experience engaging with senior leadership and translating requirements into solutions.
  • Hands-on with Power BI, Fabric, and the Microsoft BI stack.

Responsibilities

  • Lead the development and implementation of data analytics and BI strategies, mentoring and growing a team.
  • Engage with the SLT to provide actionable insights and drive data-driven decisions.
  • Oversee Fabric and Power BI deployments across units with our partner.
  • Develop and maintain data warehouses with dimensional design and indexing.
  • Manage ETL to load data into warehouses and optimize data cubes for BI projects.
  • Serve as Master Data Steward for all master data across the organisation.

Skills

Data analytics
Team leadership
Strategic thinking
Mentoring
Stakeholder engagement

Tools

Microsoft SQL Server
Azure Data Factory
Azure SQL Database
Power BI
Fabric

Job description

DB Recruitment is seeking an experienced leader to drive our data analytics and BI initiatives in Ireland. You will mentor a growing analytics team, partner with senior leadership to translate business needs into scalable solutions, and oversee the deployment of Fabric and Power BI across business units in collaboration with our implementation partner.

The role requires hands-on design and development of data warehouses, ETL pipelines, and data cubes, plus stewardship of master data within the

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