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- Tasks: Join us as a Data Engineer to build and manage data pipelines for exciting defence projects.
- Company: Be part of a mission-critical team in the Southwest UK, focused on AI and ML initiatives.
- Benefits: Enjoy flexible working options and the chance to work in a secure environment.
- Why this job: Contribute to impactful projects while collaborating with talented professionals in a dynamic setting.
- Qualifications: Must have experience in data labelling, Python, and strong knowledge of secure data handling.
- Other info: Active SC Clearance and sole British nationality are required due to project sensitivity.
The predicted salary is between 36000 - 60000 £ per year.
Location: Southwest UK (On-site/Hybrid)
Clearance: Sole British National with active SC Clearance
Engagement: Contract – Outside IR35
Overview: We are seeking a skilled Data Engineer / Data Scientist with strong experience in data labelling and imaging datasets to support a critical defence-related project in the Southwest UK. The ideal candidate will have a solid background in building and managing data pipelines, annotating and labelling image-based data for machine learning workflows, and working within secure environments. You will be a key contributor in preparing high-quality datasets to support AI and ML initiatives in a mission-critical context.
Key Responsibilities:
- Develop and maintain robust data pipelines to ingest, clean, transform, and store large volumes of imaging data.
- Lead and support the data labelling process—developing tools and workflows for efficient annotation of image and video data.
- Work closely with ML engineers and data scientists to ensure datasets are model-ready.
- Perform exploratory data analysis to identify data quality issues and labelling inconsistencies.
- Implement QA and validation processes to ensure labelling accuracy and consistency.
- Contribute to automation of labelling workflows using computer vision tools and Python-based frameworks.
- Collaborate with cross-functional teams in a secure, SC-cleared environment.
Essential Skills & Experience:
- Proven experience as a Data Engineer or Data Scientist with hands-on exposure to data labelling processes.
- Strong experience with image data, ideally in defence, aerospace, or industrial domains (e.g., satellite, UAV, thermal imaging).
- Proficient in Python and libraries such as Pandas, NumPy, OpenCV, TensorFlow, or PyTorch.
- Experience with data annotation tools (e.g., Labelbox, CVAT, VIA, or custom platforms).
- Strong knowledge of data handling best practices in secure environments.
- Experience designing and managing ETL pipelines and working with structured/unstructured data sources.
- Active SC Clearance and sole British nationality are mandatory due to project sensitivity.
Desirable:
- Experience in defence or government programmes.
- Familiarity with cloud-based ML toolsets (e.g., AWS SageMaker Ground Truth, Azure Custom Vision).
- Knowledge of computer vision models and their data requirements.
- Experience managing annotation teams or quality control processes.
Additional Details:
- This role is classified as Outside IR35.
- Candidate must be based or willing to work on-site in the Southwest UK.
- Flexible working considered depending on security and project requirements.
Contact Detail:
Experis UK Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Data Engineer (City Of Bristol)
✨Tip Number 1
Familiarise yourself with the specific data labelling tools mentioned in the job description, such as Labelbox and CVAT. Having hands-on experience with these platforms can give you a significant edge during discussions with our team.
✨Tip Number 2
Brush up on your Python skills, especially with libraries like Pandas, NumPy, and OpenCV. Being able to demonstrate your proficiency in these areas will show us that you're ready to tackle the technical challenges of the role.
✨Tip Number 3
Highlight any previous experience you have working in secure environments, particularly in defence or aerospace. This will reassure us that you understand the importance of data handling best practices in sensitive contexts.
✨Tip Number 4
If you have experience managing annotation teams or quality control processes, be sure to mention it. This kind of leadership experience is valuable for the collaborative nature of the role and will set you apart from other candidates.
We think you need these skills to ace Data Engineer (City Of Bristol)
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights relevant experience in data engineering and data science, particularly focusing on your skills in data labelling and imaging datasets. Use keywords from the job description to align your experience with the role.
Craft a Strong Cover Letter: Write a cover letter that specifically addresses the key responsibilities and essential skills mentioned in the job description. Explain how your background in building data pipelines and working with image data makes you a perfect fit for this position.
Showcase Relevant Projects: If you have worked on projects involving data labelling or machine learning workflows, be sure to include these in your application. Describe your role, the tools you used, and the outcomes of these projects to demonstrate your hands-on experience.
Highlight Security Clearance: Since active SC Clearance is mandatory for this role, make sure to clearly state your clearance status in your application. This will help the hiring team quickly identify your eligibility for the position.
How to prepare for a job interview at Experis UK
✨Showcase Your Technical Skills
Be prepared to discuss your experience with Python and relevant libraries like Pandas, NumPy, and OpenCV. Highlight specific projects where you've built data pipelines or worked with imaging datasets, as this will demonstrate your hands-on expertise.
✨Understand the Defence Context
Familiarise yourself with the defence-related aspects of the role. Research how data engineering and labelling contribute to mission-critical projects in this sector, as it will show your genuine interest and understanding of the field.
✨Prepare for Scenario-Based Questions
Expect questions that assess your problem-solving skills in real-world scenarios. Think about challenges you've faced in data labelling or pipeline management and be ready to explain how you overcame them, particularly in secure environments.
✨Emphasise Collaboration Skills
Since the role involves working closely with ML engineers and data scientists, be sure to highlight your teamwork experiences. Discuss how you've collaborated on projects, especially in cross-functional teams, to ensure datasets are model-ready.
