Posted: 15 June
The role
We are seeking an experienced Azure Data Engineer to join a global technology organization on a strategic data modernization initiative. This is an opportunity to play a key role in transforming a legacy data platform into a modern cloud-based analytics ecosystem built on Microsoft Fabric and Azure technologies.
You will be responsible for enhancing existing ETL processes, designing scalable data solutions, and driving the migration from an on-premises PostgreSQL data lake to a modern cloud architecture. Working closely with Data Management, Analytics, and Business stakeholders, you will help deliver trusted, high-quality data that powers reporting, business intelligence, and strategic decision-making.
Why Join?
Join a leading global IT services organisation
Work on a high-profile data transformation programme
Gain hands-on experience with Microsoft Fabric and modern Azure data technologies
Collaborate with talented data professionals across engineering, analytics, and governance teams
Influence the future data architecture and analytics strategy of the organisation
Key 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.
Data Quality & Governance
Implement automated data quality controls, validation rules, and monitoring within ETL and transformation workflows.
Identify, investigate, and resolve data quality issues through root-cause analysis and remediation activities.
Support Master Data Management (MDM) and reference data processes.
Collaborate with Data Stewards and business stakeholders to improve data quality, consistency, and governance.
Ensure data is sourced from approved, governed systems and aligned with enterprise data standards.
Document data pipelines, transformation logic, data models, and architectural decisions.
Contribute to the evaluation and implementation of data governance, architecture, and data quality frameworks.
Work within Agile delivery teams and collaborate effectively across technical and business functions.
Required Skills & Experience
Bachelor's Degree in Computer Science, Information Systems, Engineering, or a related discipline.
4+ years' experience in Data Engineering, Analytics Engineering, or a 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.
Salary dependent on candidate experience. Benefits: Annual Bonus Scheme. Contributory Pension. Private Medical Insurance. Life Assurance & Long‑Term Disability. Employee Assistance Programme. 22 days annual leave + 10 public holidays. Relocation package. Continuous Learning & Development. Access to extensive training & certification resources. Lunch & Learn sessions. Additional perks including company discounts, on‑site parking, and bike‑to‑work scheme
Based in Letterkenny, Co. Donegal. Hybrid (3 days onsite per week). Candidates must be eligible to work in Ireland/EU.
For more information, please contact David Coyle at 01 635 1748 or email david@methodius.com
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