Senior Data Analyst – Manufacturing Analytics (Kilkenny)

Abbott Laboratories; Kilkenny; On-site; EUR 70,000 - 90,000; Full time

Benefits offered by this job

Family health insurance

Life assurance

Fantastic new facility

Benefits package

Job summary

Abbott Laboratories in Kilkenny is seeking a Senior Data Analyst to join the Engineering Data & Analytics team at our Kilkenny manufacturing facility. You will transform complex data into meaningful insights that drive performance, and you will develop dashboards and self-service analytics for operations, engineering, quality, and supply chain.

The role focuses on supporting local site initiatives while contributing to global analytics programmes.

Qualifications

• Bachelor's degree in Engineering, Data Analytics, Statistics, Mathematics, Computer Science, or related discipline.
• Significant experience in data analytics, business intelligence, operational analytics, or engineering analytics.
• Strong analytical and problem-solving skills with experience working with complex datasets.
• Advanced SQL skills and experience querying large datasets.
• Experience developing automation and analytics solutions using Python or similar scripting/programming tools to streamline processes, integrate data sources, and support data-driven decision making.
• Ability to communicate insights effectively to both technical and business audiences.
• Experience working with cross-functional stakeholders in a fast-paced environment.

Responsibilities

• Deliver business insights by analysing manufacturing, engineering, quality, supply chain, and operational data.
• Translate complex datasets into clear and actionable insights for technical and non-technical audiences.
• Develop meaningful KPIs and performance measures that support business objectives.
• Support data-driven decision making across multiple functions within the site.
• Partner with Operations, Engineering, Quality, and Continuous Improvement teams to solve complex business challenges.
• Identify performance improvement opportunities through statistical analysis and data exploration.
• Investigate process variation, performance gaps, and root causes using structured analytical methodologies.
• Measure and track the effectiveness of improvement initiatives and operational programmes.
• Design and develop dashboards, reports, visualisations, and self-service analytics solutions.
• Work with data engineers and platform teams to ensure data is reliable, accessible, and fit for purpose.
• Support the development of advanced analytics capabilities that improve business performance.
• Help establish best practices for analytics, reporting, and business intelligence across the site.
• Act as the primary analytics representative for global Engineering Data & Analytics projects deployed to the Kilkenny site.
• Ensure global solutions are adopted with local requirements represented.
• Collaborate across Europe and the US to share insights and approaches.
• Standardise metrics, reporting, and analytical methodologies across the network.
• Present findings to engineering teams, site leadership, and global stakeholders.
• Mentor junior analysts and develop analytical capability across the organisation.
• Promote a culture of fact-based decision making and continuous improvement.

Skills

Data analytics

Business intelligence

Operational analytics

Engineering analytics

SQL

Python

Communication

Education

Bachelor's degree in Engineering, Data Analytics, Statistics, Mathematics, Computer Science, Business Analytics, or related

Tools

Databricks

Spark

Cloud analytics platforms

Job description

Abbott Laboratories in Kilkenny is seeking a Senior Data Analyst to join the Engineering Data & Analytics team at our Kilkenny manufacturing facility. You will transform complex data into meaningful insights that drive performance, and you will develop dashboards and self-service analytics for operations, engineering, quality, and supply chain.

The role focuses on supporting local site initiatives while contributing to global analytics programmes.