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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 by solving relevant problems in manufacturing and supply chains.
- Qualifications: 5+ years in data engineering, expertise in Snowflake and AWS required.
- Other info: Collaborate with a multidisciplinary team in a supportive, innovative culture.
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 employer: QAD
Contact Detail:
QAD Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Data Engineer
✨Tip Number 1
Network like a pro! Reach out to folks in the industry on LinkedIn or at local meetups. We all know that sometimes it’s not just what you know, but who you know that can help you land that Data Engineer role.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your data pipelines and projects. We recommend using platforms like GitHub to share your work. This gives potential employers a taste of what you can do with Snowflake and AWS.
✨Tip Number 3
Prepare for interviews by brushing up on your SQL and Python skills. We suggest doing mock interviews with friends or using online platforms. Being able to demonstrate your technical prowess will set you apart from the competition.
✨Tip Number 4
Apply through our website! We’re always on the lookout for talented individuals who want to join us. Make sure to tailor your application to highlight your experience with ETL/ELT and AI/ML integration, as these are key for the role.
We think you need these skills to ace Data Engineer
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 up with 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 and Python. Mention specific projects where you've implemented ETL/ELT pipelines or integrated AI models. We’re keen to see your hands-on experience!
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 services. Be ready to discuss how you've used these tools in past projects, especially focusing on data pipeline design and optimisation.
✨Showcase Your Problem-Solving Skills
Prepare examples of real-world problems you've solved in data engineering. Think about challenges related to ETL/ELT processes or integrating AI models, and be ready to explain your thought process and the impact of your solutions.
✨Understand the Business Context
Familiarise yourself with the manufacturing industry and how data engineering plays a role in adaptive manufacturing. This will help you connect your technical skills to the company's mission and demonstrate your interest in their work.
✨Ask Insightful Questions
Prepare thoughtful questions about the team dynamics, the technologies they use, and their approach to data governance. This shows your enthusiasm for the role and helps you gauge if it's the right fit for you.
