Description
Deep Digital Solutions Group (Deep DSG) is seeking a Graduate Data Engineer to 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.
Sectors
Sectors
Description
Deep Digital Solutions Group (Deep DSG) is seeking a Graduate Data Engineer to 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.
