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- Tasks: Design and optimise data pipelines in a dynamic, AI-driven environment.
- Company: Join QAD Inc., a leader in cloud-based enterprise software for global manufacturing.
- Benefits: Fully remote role with competitive salary and opportunities for professional growth.
- Why this job: Make a real impact by solving relevant problems in manufacturing and supply chains.
- Qualifications: 5+ years in data engineering, expertise in Snowflake and AWS required.
- Other info: Be part of a multidisciplinary team focused on innovation and adaptive manufacturing.
The predicted salary is between 36000 - 60000 £ per year.
QAD Inc. is a leading provider of adaptive, cloud-based enterprise software and services for global manufacturing companies. Global manufacturers face ever-increasing disruption caused by technology-driven innovation and changing consumer preferences. In order to survive and thrive, manufacturers must be able to innovate and change business models at unprecedented rates of speed. QAD calls these companies Adaptive Manufacturing Enterprises. QAD solutions help customers in the automotive, life sciences, packaging, consumer products, food and beverage, high tech and industrial manufacturing industries rapidly adapt to change and innovate for competitive advantage. We are looking for talented individuals who want to join us on our mission to help solve relevant real-world problems in manufacturing and the supply chain. This role is fully remote in the UK, with full work authorization already in effect. No Visa sponsorship is available.
Job Description
In a data-driven and AI-oriented environment, you will be responsible for the design, industrialization, and optimization of inter-application data pipelines. You will be involved in the entire data chain, from data ingestion to its use by data science teams and AI systems in production within a human-sized and multidisciplinary team. This role is within the Process Intelligence (PI) team that combines functions such as Process Mining, Real Time Monitoring and Predictive AI.
Key responsibilities:
- Design and maintain scalable data pipelines.
- Structure, transform, and optimize data in Snowflake.
- Implement multi-source ETL/ELT flows (ERP, APIs, files).
- Leverage the AWS environment, including S3, IAM, and various data services.
- Prepare data for Data Science teams and integrate AI/ML models into production.
- Ensure data quality, security, and governance.
- Provide input on data architecture.
Qualifications
- 5+ years of experience in data engineering, including significant experience in a cloud environment.
- Snowflake (MUST HAVE): Expertise in modeling, query optimization, cost management, and security.
- AWS: Strong knowledge of data and cloud services including S3, IAM, Glue, and Lambda.
- Languages: Advanced SQL and Python for data manipulation, automation, and ML integration.
- Data Engineering: Proven experience in ETL/ELT pipeline design.
- AI/ML Integration: Ability to prepare data for model training and deploy AI models into production workflows (batch or real-time).
Nice to Have:
- Experience with agentic AI architectures, including agent orchestration and decision loops.
- Integration of agent-driven AI models into existing data pipelines.
- Knowledge of modern architectures such as Lakehouse or Data Mesh.
Data Engineer in York employer: QAD
Contact Detail:
QAD Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Data Engineer in York
✨Tip Number 1
Network like a pro! Reach out to people in the industry, attend virtual meetups, and connect with fellow data enthusiasts on LinkedIn. You never know who might have the inside scoop on job openings or can refer you directly.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your data engineering projects, especially those involving Snowflake and AWS. This will give potential employers a taste of what you can do and set you apart from the crowd.
✨Tip Number 3
Prepare for interviews by brushing up on common data engineering questions and practical scenarios. Practice explaining your thought process when designing data pipelines or optimising queries – it’s all about demonstrating your problem-solving skills!
✨Tip Number 4
Don’t forget to apply through our website! We’re always on the lookout for talented individuals who are ready to tackle real-world problems in manufacturing. Your next big opportunity could be just a click away!
We think you need these skills to ace Data Engineer in York
Some tips for your application 🫡
Tailor Your CV: Make sure your CV is tailored to the Data Engineer role. Highlight your experience with Snowflake, AWS, and any relevant data engineering projects. We want to see how your skills match what we're looking for!
Craft a Compelling Cover Letter: Your cover letter is your chance to shine! Share your passion for data engineering and how you can contribute to our mission at QAD. Be sure to mention specific experiences that relate to the job description.
Showcase Your Technical Skills: Don’t forget to showcase your technical skills in SQL and Python. We love seeing examples of how you've used these languages in real-world scenarios, especially in cloud environments like AWS.
Apply Through Our Website: We encourage you to apply through our website for the best chance of getting noticed. It’s super easy, and we can’t wait to see your application come through!
How to prepare for a job interview at QAD
✨Know Your Data Tools
Make sure you brush up on your knowledge of Snowflake and AWS services like S3 and IAM. Be ready to discuss how you've used these tools in past projects, especially in designing and optimising data pipelines.
✨Showcase Your ETL/ELT Experience
Prepare specific examples of ETL/ELT flows you've implemented. Talk about the challenges you faced and how you overcame them, as well as the impact your work had on data quality and governance.
✨Demonstrate AI/ML Integration Skills
Be ready to explain how you've prepared data for AI/ML models and integrated them into production workflows. Highlight any experience with real-time data processing and the benefits it brought to your previous teams.
✨Ask Insightful Questions
Prepare thoughtful questions about QAD's approach to adaptive manufacturing and how they leverage data in their solutions. This shows your genuine interest in the role and helps you understand if it's the right fit for you.
