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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 software for global manufacturing.
- Benefits: Fully remote role with competitive salary and opportunities for growth.
- Why this job: Make a real impact on manufacturing innovation and tackle real-world challenges.
- Qualifications: 5+ years in data engineering, expertise in Snowflake and AWS required.
- Other info: Collaborate with a multidisciplinary team in a supportive, human-sized environment.
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.
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.
- 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 Warrington employer: QAD
Contact Detail:
QAD Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Data Engineer in Warrington
✨Network Like a Pro
Get out there and connect with folks in the industry! Attend meetups, webinars, or even just grab a coffee with someone who works at QAD or in data engineering. Building relationships can open doors that a CV just can't.
✨Show Off Your Skills
Don’t just talk about your experience; demonstrate it! Create a portfolio showcasing your data pipelines, projects, or any cool stuff you've built. This gives potential employers a taste of what you can do and sets you apart from the crowd.
✨Ace the Interview
Prepare for those interviews by brushing up on your technical skills and understanding QAD's mission. Be ready to discuss how your experience aligns with their needs, especially around Snowflake and AWS. Confidence is key!
✨Apply Through Our Website
Make sure to apply directly through our website! It’s the best way to ensure your application gets seen by the right people. Plus, it shows you're genuinely interested in joining the QAD team.
We think you need these skills to ace Data Engineer in Warrington
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! Use it to explain why you're passionate about data engineering and how you can contribute to our mission at QAD. Keep it concise but impactful – we love a good story!
Showcase Your Technical Skills: Don’t forget to showcase your technical skills in SQL, Python, and ETL/ELT pipeline design. We’re keen on seeing how you’ve used these skills in real-world scenarios, so be specific about your achievements!
Apply Through Our Website: We encourage you to apply through our website for a smoother application process. It helps us keep track of your application and ensures you don’t miss out on any important updates from us!
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 before the interview. Be ready to discuss your experience with data pipelines, ETL/ELT processes, and how you've optimised data in previous roles. This will show that you're not just familiar with the tools, but that you can leverage them effectively.
✨Showcase Your Problem-Solving Skills
QAD is all about solving real-world problems in manufacturing. Prepare examples from your past work where you tackled complex data challenges or improved processes. Highlight your thought process and the impact of your solutions to demonstrate your value as a Data Engineer.
✨Understand the Business Context
Familiarise yourself with the manufacturing industry and the specific challenges it faces. Knowing how data engineering fits into the bigger picture of adaptive manufacturing will help you connect your technical skills to their mission, making you a more appealing candidate.
✨Prepare Questions for Them
Interviews are a two-way street! Prepare insightful questions about the team dynamics, the technologies they use, and how they approach data governance. This shows your genuine interest in the role and helps you assess if QAD is the right fit for you.
