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Graduate data engineer

Dungarvan
Deep Dsg
Data engineer
Posted: 20 March
Offer description

Graduate Data Engineer Position
Deep Digital Solutions Group (Deep DSG) is seeking a Graduate Data Engineerto join our growing team supporting digital transformation initiatives with our pharmaceutical manufacturing customers.
In this role, you will help ensure accurate, reliable time-series data is collected and made available for engineering, quality, and compliance activities.
This is an excellent opportunity for a recent graduate to build hands-on experience with industrial data systems and digital technologies used in regulated industries.
Key Responsibilities
As a Graduate Data Engineer, you will:
Assist with the setup and basic configuration of the Aveva PI (or similar) data historian system.
Support data collection, validation, and organisation of time-series data from manufacturing equipment.
Help monitor historian performance and report issues to senior engineers.
Create and maintain PI tags and associated metadata under guidance.
Work with automation and process teams to support reliable data flow between systems.
Contribute to simple interfaces, visualisations, or reporting solutions using historical data.
Follow data integrity, security, and compliance procedures.
Maintain clear documentation for configurations, updates, and system changes.
Perform other duties as assigned.
This job description is intended to give the candidate an appreciation of the role and the range of duties; it does not attempt to detail every activity.
Job benefits:
Hybrid working
20 days Annual leave
Company pension
Medical insurance
Employee Assistance Program
Income Protection
Life Insurance
Paid sick leave
Bike to work scheme
Professional development
Must-Haves
A degree in
Computer Science
,
Electrical Engineering
, or a
related technical field
.
Interest in industrial data systems, automation, or time-series data.
Basic knowledge of SQL and/or a programming language (e.g., Python).
Strong analytical and problem-solving skills.
Willingness to learn and work in a regulated pharmaceutical environment.
Nice-to-Haves
Exposure to data historian tools (Aveva PI, OSIsoft PI, AspenTech, etc.).
Familiarity with PLCs, SCADA, MES, or automation systems.
Understanding of GxP, data integrity (ALCOA+), or validation principles.
Experience with data visualisation tools (Power BI, Tableau, etc.).
Knowledge of cloud platforms or time-series databases.
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