Data Engineer: Microsoft Fabric & Lakehouse Platform

IPL Schoeller; Dublin; On-site; EUR 70,000 - 100,000; Full time

Job summary

IPL Schoeller is seeking a Data Engineer to strengthen its BI and data capability. You will build scalable data assets, focus on pipelines, SQL transformations, data modelling, and platform reliability using Microsoft Fabric and related technologies.

In this role you will integrate data from ERP and other sources, implement data quality checks, and support semantic models and BI report development as part of a broader BI and Data team.

Qualifications

• Bachelor's degree or equivalent in Computer Science, Information Systems, Engineering or related field.
• 5+ years in data engineering or analytics engineering roles.
• Hands-on experience with SQL and data pipelines on Microsoft-centric platforms.
• Experience with data modelling, warehousing and multi-source integration.
• Experience using Power BI or Tableau for analytics consumption.

Responsibilities

• Build reliable, scalable data assets to support enterprise analytics and reporting.
• Develop, optimise and support SQL transformations and data pipelines.
• Design and maintain batch and near real-time pipelines using Microsoft Fabric and related tools.
• Create lakehouse/warehouse architectures and semantic models for dashboards.
• Collaborate with BI Manager and cross-functional teams on semantic models and reports.

Skills

SQL

Data pipelines

Microsoft Fabric

Azure Synapse

Data modelling

ETL/ELT

Power BI

Cross-functional

Education

Bachelor's degree in CS/IS/Engineering

Master's degree desirable

Tools

Microsoft Fabric

Azure Synapse

Azure Data Factory

Power BI

Job description

IPL Schoeller is seeking a Data Engineer to strengthen its BI and data capability. You will build scalable data assets, focus on pipelines, SQL transformations, data modelling, and platform reliability using Microsoft Fabric and related technologies.

In this role you will integrate data from ERP and other sources, implement data quality checks, and support semantic models and BI report development as part of a broader BI and Data team.