Ornua is an Irish dairy co-operative that markets and sells dairy products on behalf of its Members, Ireland's dairy processors and, in turn, Irish dairy farmers. Ornua is Ireland's largest exporter of Irish dairy products and has annualised sales of €3.4 billion. Headquartered in Dublin, Ornua has a strong global team of 2,900 employees, operating from 10 business units worldwide, including 13 production facilities. Ornua's core purpose is to build profitable routes to market for Irish dairy products.
The Group is structured across two divisions: Ornua Foods and Ornua Ingredients. Ornua Foods is responsible for the marketing and sales of Ornua's consumer brands, including Ireland's most successful food export, Kerrygold, as well as Kerrygold Dubliner, Pilgrims Choice, Forto and BEO milk powders.
Ornua Ingredients is responsible for the procurement of Irish and non-Irish dairy products, for the sale of dairy ingredients to food manufacturing and foodservice customers across the world, and for managing volatility through de-risking and trading strategies.
Ornua's Values
At Ornua, our Values lie at the core of everything that we do and how we behave both individually and as a business. Our five values, and their underlying behaviours, encourage us to Seek and Embrace New Ideas, Make It Happen, Be Our True Selves, Show You Care and Achieve Great Things Together.
Ornua's Growth
At Ornua, our co-operative ethos lies at the heart of how we do business. We care passionately about driving sustainable, profitable growth, underpinned by our ambitious 'Path to Prosper' strategy. We have delivered significant growth in our core business, and we have ambitious plans for continued growth over the next five years.
WHY THIS ROLE IS VALUABLE
The newly established Data & Analytics team is a pivotal group-wide function dedicated to transforming our approach to data. Our mission is to deliver data and analytics solutions that unlock the full potential of our data assets. By providing actionable insights, we empower better decision-making, enhance productivity, and drive business growth.
The Data Engineer will be responsible for designing, building, and maintaining the data services and tools needed to collect, store, and analyse data. The successful candidate will ensure that data is accessible, reliable, and ready for analysis by data scientists and business analysts.
KEY AREAS OF RESPONSIBLITY:
- Data Product/Asset Design: Collaborate with business stakeholders to gather requirements and perform data mapping, ensuring the design and development of data assets follow optimal and best practice approaches.
- Data Pipeline Development: Create and maintain optimal data pipeline architecture for extracting, transforming, and loading (ETL) data from various sources.
- Data Integration: Integrate and connect data from multiple sources to create a unified data ecosystem.
- Data Management: Ensure data quality, consistency, and security across the data lifecycle.
- Performance Optimization: Optimize data delivery and re-design infrastructure for greater scalability and efficiency.
- Collaboration: Work closely with data scientists, analysts, and other stakeholders to support their data needs and resolve data-related issues.
- Automation: Automate manual processes and improve data workflows to enhance operational efficiency.
- Operational Support: Provide ongoing operational support for data infrastructure, ensuring high availability and performance.
- Defect Management: Identify, manage, and resolve defects in data pipelines and data services in line with Service Level Agreements (SLAs).
- DataOps: Implement DataOps practices to improve the speed, quality, and reliability of data analytics. This includes fostering collaboration, automating workflows, and ensuring continuous monitoring and feedback.
KEY REQUIREMENTS:
- Technical Competence including proficiency in Microsoft data analytical and BI tools, including SQL Server (SS), SS Integration Services (SSIS), SS Reporting Services, Power BI service, Power BI desktop, Power BI gateway configuration, Power BI workspaces, organizational apps, MS Visual Studio, MS Visual Code, GitHub source control, and Azure DevOps.
- Experience with cloud-based data services, including Azure Data Factory (ADF), data pipelines, notebooks, PySpark, Spark SQL, Microsoft Fabric, Databricks Data Lakehouse, Snowflake and OneLake.
- Bachelor or Master's degree in computer science, Engineering, or a related field. Relevant certifications in data engineering or cloud platforms (e.g. Azure Data Engineer Associate, AWS Certified Data Analytics, Google Cloud Professional Data Engineer)) are a plus.
- Experience in development across a multi-environment platform and associated governance on deployment through the product lifecycle (Dev-Test-Production).
- Excellent knowledge of SQL relational database query language, including views, tables, SQL functions, CTEs, dynamic SQL, stored procedures, and parameterization.
- Excellent knowledge of data modelling concepts, techniques, and Kimball design.
- Strong knowledge of metadata frameworks for extracting and loading data for scalability.
- Good knowledge of ETL/ELT logical architectures.
- Proficiency with Power BI DAX and M languages, including strong knowledge of DAX queries, query plans, formula engine, storage engine (Vertipaq), and operational performance.
- Awareness of ERP modules and business processes, and how they integrate across various functions such as finance, procurement, supply chain, quality assurance, and sales.
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