Senior Business & Data Analyst

Circet; Clondalkin; On-site; EUR 70,000 - 110,000; Full time

Job summary

Circet Ireland & UK is seeking a Senior Business and Data Analyst to join our data and analytics team in Clondalkin. You will collect, transform, analyse, and visualise data to support strategic decisions, design scalable reporting solutions, and develop semantic models on the Microsoft Fabric platform.

Strong SQL, Power BI, and Fabric experience are essential. You will collaborate with IT and business stakeholders to translate requirements into technical solutions, deliver dashboards, and help

Qualifications

• Experience as a Data Analyst or BI Analyst.

Responsibilities

• Collect, analyse and interpret data from multiple systems.
• Create interactive Power BI reports and dashboards.
• Develop Fabric workspaces and semantic models.
• Build data pipelines using Fabric Data Factory.
• Ensure data quality and governance standards.
• Engage with business users to gather requirements.
• Identify opportunities for automating reporting processes.
• Improve data models and reporting architecture.

Skills

Power BI

SQL

Microsoft Fabric

Semantic models

ETL/ELT pipelines

Data modelling

Data analysis

Stakeholder management

Communication

Problem solving

Tools

Fabric Data Factory

Dataflows Gen2

Lakehouse architecture

Azure SQL

Git/Azure DevOps

Python

Spark

Job description

Position : Senior Business and Data Analyst

Location : Clondalkin, Dublin 22

Employment Type: Full-time

Overview

Circet Ireland & UK are seeking a motivated and detail-oriented Data Analyst with experience in Microsoft Fabric to join our growing data and analytics team. The successful candidate will be responsible for collecting, transforming, analysing, and visualising data to support strategic and operational decision-making. Working closely with business stakeholders, the Data Analyst will design scalable reporting solutions, develop semantic models, and ensure high standards of data quality and governance using the Microsoft Fabric platform. The ideal candidate will have strong analytical skills, experience with Power BI, SQL, and Microsoft Fabric technologies, and the ability to translate complex business requirements into meaningful insights.

Key Responsibilities

Data Analysis & Reporting

• Collect, analyse, and interpret data from multiple business systems.
• Design, develop, and maintain interactive Power BI reports and dashboards.
• Produce recurring operational and management reports.
• Identify trends, anomalies, and opportunities through data analysis.
• Present findings and recommendations to technical and non-technical stakeholders.

Microsoft Fabric Development

• Develop and maintain Microsoft Fabric workspaces and analytics solutions.
• Build and manage Fabric Lakehouses, Warehouses, and Dataflows Gen2.
• Create and maintain semantic models for enterprise reporting.
• Develop data pipelines using Fabric Data Factory.
• Work with Fabric Notebooks where appropriate for data preparation and analysis.
• Monitor Fabric workloads and optimise performance and resource utilisation.

Data Engineering & Integration

• Extract, transform, and load (ETL/ELT) data from various internal and external sources.
• Develop reusable data transformation processes.
• Integrate cloud and on-premise data sources into Microsoft Fabric.
• Ensure data consistency and integrity across reporting platforms.

Data Quality & Governance

• Monitor data quality and investigate inconsistencies.
• Support implementation of data governance standards.
• Maintain data dictionaries and metadata documentation.
• Ensure compliance with organisational security and privacy policies.
• Assist with data lineage and auditing within Microsoft Fabric.

Business Engagement

• Gather reporting requirements from business users.
• Translate business needs into technical solutions.
• Deliver training and support to end users.
• Promote data-driven decision making across the organisation.
• Work closely with IT, business analysts, and operational teams.

Continuous Improvement

• Identify opportunities to automate manual reporting processes.
• Recommend improvements to data models and reporting architecture.
• Keep up to date with Microsoft Fabric capabilities and best practices.
• Contribute to the organisation's analytics strategy and standards.

Required Skills & Experience

Essential

• Experience working as a Data Analyst or Business Intelligence Analyst.
• Hands-on experience withMicrosoft Fabric.
• Strong Power BI report development experience.
• Excellent SQL skills.
• Experience developing semantic models.
• Experience building ETL/ELT pipelines.
• Strong understanding of relational databases and data modelling.
• Experience working with large datasets.
• Excellent analytical and problem-solving skills.
• Strong communication and stakeholder management abilities.
• Ability to manage multiple priorities and deadlines.

Technical Skills

• Microsoft Fabric
• Power BI
• SQL Server / Azure SQL
• Fabric Data Factory
• Lakehouse architecture
• Data Warehouses
• Dataflows Gen2
• DAX
• Power Query (M)
• Microsoft Excel
• Git or Azure DevOps (desirable)
• Python or Spark (desirable)

Desirable Experience

• Microsoft Certified: Fabric Analytics Engineer Associate (DP-600).
• Experience with Azure Data Lake Storage.
• Experience with Microsoft Purview.
• Knowledge of Microsoft Synapse Analytics.
• Experience with Power Automate.
• Understanding of Data Governance frameworks.
• Experience with REST APIs and data integration.
• Familiarity with Agile/Scrum methodologies through DevOps
• Knowledge of Claris Filemaker would be an advantage

Personal Attributes

• Highly analytical and naturally curious.
• Strong attention to detail.
• Excellent organisational skills.
• Self-motivated and proactive.
• Strong customer and stakeholder focus.
• Able to explain technical concepts clearly.
• Team player with a collaborative approach.
• Committed to continuous learning and professional development.

Key Deliverables

• Enterprise Power BI dashboards.
• Microsoft Fabric analytics solutions.
• Reliable and automated data pipelines.
• Accurate business reporting.
• High-quality semantic models.
• Well-documented data assets.
• Improved data quality and governance.
• Actionable business insights that support operational and strategic decision-making.