Data Analyst – Manufacturing & Digital Enablement
At Siemens Healthineers, we pioneer breakthroughs in healthcare. Our technologies support clinicians and care teams around the world to make confident decisions and deliver better outcomes for patients. Behind this mission sits a strong operational backbone, where data, insight and digital capability play a vital role in shaping how we work today and how we build the factory of the future. We are now looking for a Data Analyst to join our manufacturing enablement environment. This is a hands‑on role for someone who enjoys being close to operations, building trusted data foundations, and turning practical insights into real improvements on the shop floor.
About the role:
This role sits at the intersection of manufacturing processes and data analytics. You will focus on how operational data is captured, structured and used across manufacturing and supply chain activities. Rather than working purely with existing datasets, you will help shape how data is collected in the first place — from systems, sensors and physical tools — and ensure it is reliable, meaningful and trusted. You will work as an individual contributor, collaborating closely with manufacturing, enablement and IT teams. Your work will help establish the foundations for future digital transformation initiatives, including advanced analytics and automation.
What you’ll be doing:
- Designing and implementing data collection approaches across manufacturing and supply chain environments, including system‑based and physical data sources
- Deploying and integrating analytics solutions such as dashboards, KPIs and monitoring tools into day‑to‑day operational workflows
- Configuring, validating and maintaining data pipelines to ensure accuracy, consistency and availability of operational data
- Supporting the deployment of performance dashboards covering areas such as productivity, quality, yield, scrap and schedule adherence
- Working directly with end users on the shop floor and in enablement teams to support adoption, training and effective use of data tools
- Acting as a first point of contact for troubleshooting data and analytics issues, escalating where required
- Maintaining clear documentation for data flows, KPI definitions and user guidance
- Performing root‑cause analysis on data‑related operational issues and translating findings into practical recommendations
- Gathering feedback from users and continuously improving solutions to better support operational decision‑making
- Supporting standardisation of KPIs and reporting across sites and contributing to continuous improvement initiatives
What skills and experience you’ll bring:
- Experience working with data and analytics in a manufacturing, industrial or supply chain environment
- Hands‑on experience with business intelligence and visualisation tools such as Power BI
- Familiarity with data integration and pipeline concepts, including tools and platforms such as Azure, SQL, APIs and SAP data structures
- An understanding of how operational data is generated on the shop floor and how it can be used to improve performance
- The ability to translate complex data into clear, practical insights for a range of stakeholders
- Strong communication and collaboration skills, with confidence working across technical and non‑technical teams
- A structured, curious and improvement‑focused mindset
- A degree or equivalent experience in Data Analytics, Industrial Engineering, Supply Chain or a related discipline
What’s on offer:
- Competitive base salary
- 26 days annual leave with the option to buy up to 10 and sell up to 5
- Up to 10% matched pension contributions
- BUPA Private Medical insurance
- Bonus & Share Save Scheme
- Free to use on‑site gym
- 2 paid volunteering days a year
Siemens Healthineers are proud to be a Disability Confident Committed employer. If you require any adjustments at any stage of the recruitment process, please let us know.
We care about your data privacy and take compliance with GDPR as well as other data protection legislation seriously.
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