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- Tasks: Enable AI capabilities and enhance self-service analytics across the company.
- Company: Leading global supply chain organisation with a focus on innovation.
- Benefits: Competitive salary, flexible working options, and opportunities for professional growth.
- Why this job: Join a cutting-edge team and make a real impact in AI analytics.
- Qualifications: 3+ years in analytics or data engineering with expertise in modern data tools.
- Other info: Exciting environment with continuous improvement and career advancement opportunities.
The predicted salary is between 43200 - 72000 £ per year.
A leading global supply chain organisation is seeking a Solutions Engineer specializing in Natural Language Querying to enable AI capabilities and enhance self-service analytics across the company. This role requires over 3 years in analytics or data engineering, along with expertise in modern data models and tools such as DBT, Power BI, and advanced SQL.
The successful candidate will lead customer onboarding and continuously improve the data ecosystem, working in an exciting and cutting-edge environment.
NLQ Solutions Engineer for AI Analytics & LLM in Leeds employer: KDR Talent Solutions
Contact Detail:
KDR Talent Solutions Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land NLQ Solutions Engineer for AI Analytics & LLM in Leeds
✨Tip Number 1
Network like a pro! Reach out to folks in the industry, especially those already working in AI analytics. A friendly chat can open doors and give you insights that might just land you that Solutions Engineer role.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your work with DBT, Power BI, and SQL. This is your chance to demonstrate your expertise in modern data models and how you can enhance self-service analytics.
✨Tip Number 3
Prepare for interviews by brushing up on common questions related to AI capabilities and customer onboarding. We recommend practising your responses with a friend or even in front of the mirror to boost your confidence.
✨Tip Number 4
Don’t forget to apply through our website! It’s the best way to ensure your application gets noticed. Plus, we love seeing candidates who are proactive about their job search!
We think you need these skills to ace NLQ Solutions Engineer for AI Analytics & LLM in Leeds
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights your experience in analytics and data engineering. We want to see how your skills with tools like DBT, Power BI, and SQL align with what we're looking for!
Craft a Compelling Cover Letter: Your cover letter is your chance to shine! Tell us why you're passionate about AI capabilities and self-service analytics. We love hearing about your journey and what excites you about this role.
Showcase Relevant Projects: If you've worked on projects that involved modern data models or customer onboarding, make sure to mention them! We’re keen to see how you’ve contributed to improving data ecosystems in the past.
Apply Through Our Website: We encourage you to apply directly through our website. It’s the best way for us to receive your application and ensures you don’t miss out on any important updates from us!
How to prepare for a job interview at KDR Talent Solutions
✨Know Your Tech Inside Out
Make sure you’re well-versed in the tools mentioned in the job description, like DBT, Power BI, and advanced SQL. Brush up on your technical skills and be ready to discuss how you've used these tools in past projects.
✨Showcase Your Analytics Experience
With over 3 years in analytics or data engineering required, prepare specific examples of your previous work. Highlight any successful projects where you’ve enabled AI capabilities or improved self-service analytics.
✨Understand the Company’s Needs
Research the company’s supply chain operations and think about how your role as a Solutions Engineer can enhance their data ecosystem. Be ready to discuss how you can lead customer onboarding and drive continuous improvement.
✨Prepare for Scenario-Based Questions
Expect questions that assess your problem-solving skills in real-world scenarios. Think about challenges you’ve faced in analytics and how you overcame them, especially in a fast-paced environment.