Senior Data Engineer — Manufacturing Data Platform

Abbott Laboratories; Kilkenny; On-site; EUR 90,000 - 120,000; Full time

Benefits offered by this job

Family health insurance

Excellent pension scheme

Life assurance

Career development

Fantastic new facility

Job summary

Abbott Diabetes Care Kilkenny seeks a senior data engineering leader to design and deliver scalable data pipelines and analytics solutions. You will help build our Databricks platform, define standards, and collaborate with IT, cybersecurity, and manufacturing teams across Europe and the US.

The role focuses on enabling data-driven manufacturing, AI-ready data foundations, and enterprise analytics to drive operational excellence. Strong Python/SQL, Spark, and cloud experience are essential.

Qualifications

• Bachelor's degree in Engineering, Computer Science, Data Engineering, Software Engineering, Mathematics, Statistics, or a related technical discipline.
• Significant experience in Data Engineering, Data Platform Development, or Industrial Analytics.
• Strong experience designing and developing scalable data pipelines using Python and SQL.
• Experience with cloud-based data platforms and modern data architectures.
• Strong understanding of data modelling, data integration, and data quality principles.
• Proven experience delivering technical projects in complex business environments.
• Excellent communication, collaboration, and stakeholder management skills.
• Ability to work effectively with global teams across multiple functions and geographies.
• Hands-on experience with Databricks and Apache Spark.
• Experience with Delta Lake, Unity Catalog, and Lakehouse architecture principles.
• Experience with Microsoft Azure data services.
• Experience supporting AI, Data Science, Machine Learning, or advanced analytics initiatives.
• Experience integrating Operational Technology (OT) and Information Technology (IT) systems and data.
• Experience within Medical Devices, Pharmaceuticals, Life Sciences, Manufacturing, or other regulated industries.
• Knowledge of MES, SCADA, Historian, ERP, or other industrial systems.
• Experience implementing data governance and data management frameworks.

Responsibilities

• Design, develop, and maintain scalable data pipelines and data products supporting engineering, manufacturing, quality, and operational analytics.
• Develop robust ETL/ELT frameworks to ingest, transform, and deliver data from a wide range of enterprise and manufacturing systems.
• Implement and optimize cloud-based data solutions using Databricks, Apache Spark, and modern Lakehouse architecture principles.
• Ensure data quality, reliability, security, and governance across the entire data lifecycle.
• Create reusable, maintainable, and well-documented data engineering solutions that support long-term business scalability.
• Lead multiple concurrent projects from concept through deployment.
• Manage project scope, timelines, risks, and stakeholder expectations.
• Collaborate with engineering, operations, quality, IT, and business teams across multiple global regions.
• Translate business challenges into scalable technical solutions that deliver measurable value.
• Act as a subject matter expert for data engineering and modern data platform technologies.
• Mentor and support engineers, analysts, and data professionals across the organisation.
• Drive adoption of industry best practices and emerging technologies.
• Contribute to the long-term Engineering Data & Analytics strategy and roadmap.

Skills

Strong communication

Stakeholder management

Team collaboration

Problem solving

Education

Bachelor's degree

Tools

Databricks

Apache Spark

Python

SQL

Delta Lake

Unity Catalog

Lakehouse

Azure Data Services

Job description

Abbott Diabetes Care Kilkenny seeks a senior data engineering leader to design and deliver scalable data pipelines and analytics solutions. You will help build our Databricks platform, define standards, and collaborate with IT, cybersecurity, and manufacturing teams across Europe and the US.

The role focuses on enabling data-driven manufacturing, AI-ready data foundations, and enterprise analytics to drive operational excellence. Strong Python/SQL, Spark, and cloud experience are essential.