Azure Data Engineer: Cloud Modernization & Fabric Expert

Methodius IT Recruitment; Ulster; Hybrid; EUR 75,000 - 95,000; Full time

Benefits offered by this job

Annual bonus

Contributory pension

Private medical insurance

Life assurance

Long-term disability

Employee assistance programme

Annual leave 22 + 10 holidays

Relocation package

Training & certification

Lunch & learning sessions

Company discounts

On-site parking

Bike-to-work

Job summary

Methodius IT Recruitment is seeking an experienced Azure Data Engineer to join a global tech organization in a data modernization initiative. You will help transform a legacy data platform into a modern cloud analytics ecosystem built on Microsoft Fabric and Azure technologies.

You will design scalable data pipelines, migrate on-prem PostgreSQL data lake to cloud, optimise Power BI models, and collaborate with stakeholders across governance, analytics, and engineering.

Qualifications

• Bachelor's degree in Computer Science, Information Systems, Engineering, or related discipline.
• 4+ years' experience in Data Engineering, Analytics Engineering, or related field.
• Strong expertise in SQL, including complex transformations, query optimisation, and data modelling.
• Experience building and supporting ETL/ELT pipelines in on-premises, hybrid, or cloud environments.
• Strong experience with PostgreSQL, SQL Server, MySQL, or similar relational database platforms.
• Experience delivering data platform modernisation or cloud migration projects.
• Hands-on experience with Microsoft Azure and/or Microsoft Fabric.
• Knowledge of modern data lake, lakehouse, and data warehouse architectures.
• Experience with Python, Spark, or other modern data engineering technologies.
• Understanding of data governance, data quality, metadata management, and MDM concepts.
• Strong analytical and problem-solving skills.
• Excellent communication skills with the ability to translate business requirements into technical solutions.
• Self-motivated and comfortable working in fast-paced, evolving environments.
• Microsoft Fabric certification (DP-600 and/or DP-700).
• Experience with Microsoft Fabric Lakehouse, Data Factory Pipelines, Data Engineering, and Real-Time Analytics workloads.
• Experience within Financial Services, Asset Management, Investment Management, or Capital Markets environments.
• Exposure to enterprise data governance platforms and data quality tooling.

Responsibilities

• Support, maintain, and enhance existing ETL pipelines within an on-premises PostgreSQL data lake environment.
• Lead the migration of data ingestion, transformation, and orchestration processes to Microsoft Fabric using cloud-native best practices.
• Design, develop, and optimise scalable data pipelines that support enterprise analytics and reporting requirements.
• Build and maintain robust SQL-based transformation logic, including views, stored procedures, functions, and analytical datasets.
• Develop and optimise data models across lakehouse, dimensional, and relational architectures.
• Create and maintain data structures that support reporting and self-service analytics.
• Develop and optimise Power BI semantic models and datasets.
• Work closely with analytics and reporting teams to ensure data solutions are performant, scalable, and business-focused.
• Enable reliable business insights through efficient aggregation and transformation of data from multiple sources.

Skills

SQL

ETL pipelines

PostgreSQL

Python

Spark

Data governance

MDM concepts

Communication skills

Analytical thinking

Azure/Microsoft Fabric

Education

Bachelor's degree

Tools

Azure

Microsoft Fabric

Power BI

Data Factory

Job description

Methodius IT Recruitment is seeking an experienced Azure Data Engineer to join a global tech organization in a data modernization initiative. You will help transform a legacy data platform into a modern cloud analytics ecosystem built on Microsoft Fabric and Azure technologies.

You will design scalable data pipelines, migrate on-prem PostgreSQL data lake to cloud, optimise Power BI models, and collaborate with stakeholders across governance, analytics, and engineering.