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- Tasks: Manage data sources, validate quality, and develop data tools for testing environments.
- Company: Join a leading tech firm focused on innovative data solutions and quality assurance.
- Benefits: Enjoy flexible working options, professional development opportunities, and a collaborative culture.
- Why this job: Be part of a dynamic team driving data excellence and making a real impact in technology.
- Qualifications: Experience in data management, programming (Python preferred), and cloud platforms like AWS or Google Cloud.
- Other info: Ideal for those passionate about data quality and eager to learn in a supportive environment.
The predicted salary is between 36000 - 60000 £ per year.
Looking for Data Management Specialist deployed to Onsite Client OEM:
- JD: Be responsible in data sources and data acquisition, data quality validation, data pipeline, data storage and data visualisation for physical test environment.
- Delivering data quality reviews in order to support programme targets and prove out chosen technologies.
- Develop calculations, parameterisation, regulations and process of in-house data tool development.
- Be responsible for confirming the facility is performing in repeatable and reproducible measurements compliant to regulations.
- Carry out correlation exercises between test facilities and test beds across test operation.
- Ensure continuous improvement of measurement quality by reviewing the measurement equipment, systems and methods used by providing data.
- Perform calculation and evaluation of test results, particularly of results from internal correlation measurements, and initiate corrective measures as required.
- Cooperate in projects for improving test bed consistency and repeatability (together with experts from internal departments and the Instrumentation & Test Systems business unit).
- Working closely with the subject matter expert for Data Quality ensuring that the team KPI’s for Data Quality are met
- Recommend and justify process and other improvements to enable improved quality of data
- Research, communicate and implement best practice data quality methods and improve test field efficiency.
- Investigate best ways of working to make full use of equipment capability in order to improve data quality
- To continually encourage a growth mind-set across the team
- Coaching and facilitating in best technical practice, knowledge, methods in data validation and management for apprentice, new starter and existing team member development.
- Designing applications in different programming languages (preferable Python)
- Build data systems & pipelines, data validation and management in cloud platforms (AWS, Google Cloud).
- Data analysis skills, including hypothesis testing, uncertainty analysis, and process variation.
Data Management Specialist employer: Onward Technologies Limited
Contact Detail:
Onward Technologies Limited Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Data Management Specialist
✨Tip Number 1
Familiarise yourself with the specific data management tools and technologies mentioned in the job description, such as AWS and Google Cloud. Having hands-on experience or relevant projects to discuss can really set you apart during interviews.
✨Tip Number 2
Brush up on your programming skills, especially in Python, as it's preferred for this role. Consider working on personal projects or contributing to open-source projects that involve data pipelines and validation to showcase your abilities.
✨Tip Number 3
Network with professionals in the data management field, particularly those who have experience in quality validation and data acquisition. Engaging in discussions or attending relevant meetups can provide insights and potentially lead to referrals.
✨Tip Number 4
Prepare to discuss your approach to continuous improvement and how you've implemented best practices in previous roles. Be ready to share examples of how you've enhanced data quality or efficiency in past projects.
We think you need these skills to ace Data Management Specialist
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights relevant experience in data management, data quality validation, and programming skills, particularly in Python. Use specific examples that demonstrate your ability to handle data pipelines and storage.
Craft a Strong Cover Letter: In your cover letter, express your enthusiasm for the role and how your background aligns with the responsibilities outlined in the job description. Mention your experience with cloud platforms like AWS or Google Cloud and your approach to continuous improvement in data quality.
Showcase Relevant Projects: If you have worked on projects involving data analysis, validation, or system design, be sure to include these in your application. Describe your role, the technologies used, and the outcomes achieved to demonstrate your capabilities.
Highlight Soft Skills: Don't forget to mention your soft skills, such as teamwork, coaching, and communication. These are crucial for collaborating with experts and facilitating best practices within the team, as mentioned in the job description.
How to prepare for a job interview at Onward Technologies Limited
✨Understand the Role
Make sure you thoroughly understand the responsibilities of a Data Management Specialist. Familiarise yourself with data sources, data quality validation, and data pipelines. This will help you answer questions confidently and demonstrate your knowledge.
✨Showcase Your Technical Skills
Be prepared to discuss your experience with programming languages, especially Python, and cloud platforms like AWS or Google Cloud. Highlight any projects where you've built data systems or pipelines, as this will show your practical skills.
✨Prepare for Scenario-Based Questions
Expect questions that assess your problem-solving abilities in real-world scenarios. Think about how you would handle data quality issues or improve measurement consistency. Use examples from your past experiences to illustrate your thought process.
✨Emphasise Continuous Improvement
Demonstrate your commitment to continuous improvement by discussing how you've previously implemented best practices in data management. Share specific instances where you've contributed to enhancing data quality or efficiency in your previous roles.
