Data Engineer, Microsoft Data Platform

IPL Schoeller

Dublin

In loco

EUR 70.000 - 100.000

Tempo pieno

14 giorni+
Generatore di candidature

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Descrizione del lavoro

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.

Competenze

  • 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.

Mansioni

  • 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.

Conoscenze

SQL
Data pipelines
Microsoft Fabric
Azure Synapse
Data modelling
ETL/ELT
Power BI
Cross-functional

Formazione

Bachelor's degree in CS/IS/Engineering
Master's degree desirable

Strumenti

Microsoft Fabric
Azure Synapse
Azure Data Factory
Power BI

Descrizione del lavoro

Who We Are

On July 1, 2025, IPL Plastics merged with Schoeller Allibert to form IPL Schoeller (the ‘company’). The Company’s operations are split across North America (11 manufacturing plants) and Europe (16 manufacturing plants).

Who We Are

On July 1, 2025, IPL Plastics merged with Schoeller Allibert to form IPL Schoeller (the ‘company’). The Company’s operations are split across North America (11 manufacturing plants) and Europe (16 manufacturing plants). The company is headquartered in Dublin, Ireland. IPL Schoeller is a leading manufacturer of sustainable rigid packaging solutions across a range of end market segments including returnable transit packaging, consumer and industrial packaging, environmental containers and agricultural packaging. The company employs c.4,100 employees across North America (1,600 employees) and Europe (2,500 employees.)

The role
  • As a Data Engineer, you will strengthen IPL Schoeller’s internal data engineering capability as the BI and data function continues to move from traditional report development towards governed enterprise data platforms. The role is focused on building reliable, scalable and well documented data assets that support Microsoft Fabric adoption, enterprise analytics and operational reporting.
  • Act as a hands‑on mid‑level data engineer within the BI and Data team, with primary focus on data pipelines, SQL transformation logic, data modelling and platform reliability.
  • Design, build and maintain batch and near real‑time data pipelines using Microsoft Fabric, Synapse, Azure Data Factory or similar Microsoft data platform technologies.
  • Develop, optimise and support SQL based transformations, ingestion routines, stored procedures and curated data structures across structured and semi‑structured data sources.
  • Build and maintain lakehouse, warehouse and staged data architectures that support reusable enterprise datasets, semantic models, dashboards and downstream operational use cases.
  • Apply sound data modelling practices, including dimensional modelling, source‑to‑target mapping and calculation logic aligned to reporting and analytical requirements.
  • Integrate data from ERP, finance, operational systems, APIs, files and external platforms into governed enterprise data assets.
  • Implement data quality checks, reconciliation controls and monitoring routines to improve accuracy, trust and repeatability across data pipelines and reporting outputs.
  • Monitor pipeline runs, investigate failures and troubleshoot performance issues across ingestion, transformation, storage and refresh layers.
  • Support optimisation of query performance, data refresh strategies, partitioning and processing efficiency as the Microsoft Fabric platform becomes embedded across the business.
  • Working with the BI Manager, assist in the development of semantic models and BI report builds as required, while recognising that BI report development is a supporting activity rather than the primary function of the role.
  • Contribute to development standards, documentation, release management, version control and structured ways of working across the BI and Data team
  • Support security, governance and access controls across the data platform in line with internal IT and data governance standards.
  • Participate in continuous improvement initiatives to reduce manual data handling, improve platform resilience and support a stronger data engineering capability in the organisation.
What You Will Bring To The Role
  • Bachelor’s degree in Computer Science, Information Systems, Engineering, Mathematics, or a related discipline
  • Equivalent experience in data engineering, ETL/ELT development, or cloud data platform delivery will be highly advantageous
  • Master’s degree desirable.
  • 5+ years of experience in data engineering, database development, analytics engineering, or similar data platform roles.
  • Hands‑on experience with SQL and building data pipelines in Microsoft-centric platforms, including Microsoft Fabric, Azure Synapse, Azure Data Factory, or other related technologies.
  • Experience working with data modelling, data warehousing, and integrating multiple source systems.
  • Experience working with Power BI or Tableau for downstream analytics and reporting consumption.
  • Experience working across cross‑functional teams in a global or matrix organisation is advantageous
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