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- Tasks: Architect and build scalable data pipelines for an exciting new AI product.
- Company: Leading technology AI brand with a focus on innovation.
- Benefits: Competitive salary, equity package, and opportunities for professional growth.
- Why this job: Join a dynamic team and shape the future of AI technology.
- Qualifications: 7+ years in data engineering with strong pipeline design skills.
- Other info: Collaborative environment with a focus on cutting-edge technology.
The predicted salary is between 60000 - 84000 £ per year.
Our client, a global technology leader, is currently looking for a Senior/Lead Data Engineer to work with the dev team to guide the provision of Software Development for an exciting new AI product.
Key Responsibilities:
- Architect and build scalable data pipelines and infrastructure.
- Design and maintain data ingestion, transformation, and storage architectures for operational and AI workloads.
- Develop and manage batch and Real Time data pipelines.
- Build and optimize systems for vector search, retrieval, and ML data pipelines.
- Ensure data reliability, security, and governance across the platform.
- Collaborate with AI and Back End engineering teams to support training, inference, and product features.
- Implement monitoring, observability, and data quality frameworks.
Core Experience:
- 7+ years of experience in data engineering or Back End engineering roles.
- Strong experience designing and building data pipelines and distributed data systems.
- Experience working with relational databases (PostgreSQL preferred).
Lead Python Data Engineer - Leading Technology AI Brand employer: MLR Associates
Contact Detail:
MLR Associates Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Lead Python Data Engineer - Leading Technology AI Brand
✨Tip Number 1
Network like a pro! Reach out to your connections in the tech industry, especially those who work with AI and data engineering. A friendly chat can lead to insider info about job openings that aren't even advertised yet.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your best projects, especially those involving data pipelines and AI. This gives potential employers a taste of what you can do and sets you apart from the crowd.
✨Tip Number 3
Prepare for interviews by brushing up on your technical knowledge and soft skills. Practice common interview questions related to data engineering and be ready to discuss your past experiences in detail.
✨Tip Number 4
Don't forget to apply through our website! We have loads of exciting opportunities, and applying directly can sometimes give you an edge. Plus, it’s super easy to keep track of your applications!
We think you need these skills to ace Lead Python Data Engineer - Leading Technology AI Brand
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights your experience in data engineering and aligns with the key responsibilities mentioned in the job description. We want to see how your skills fit perfectly 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 AI and how your background makes you the ideal candidate for this role. Let us know what excites you about working with our team.
Showcase Relevant Projects: If you've worked on any projects that involved building data pipelines or optimising systems, make sure to mention them. We love seeing real-world examples of your work that demonstrate your expertise!
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 our team!
How to prepare for a job interview at MLR Associates
✨Know Your Data Pipelines
Make sure you can talk confidently about your experience with data pipelines. Be ready to discuss specific projects where you've designed and built scalable data architectures, as this is crucial for the role.
✨Brush Up on AI Workloads
Since the position involves working with AI products, it’s essential to understand how data ingestion and transformation work for AI workloads. Prepare examples of how you've collaborated with AI teams in the past.
✨Showcase Your Technical Skills
Be prepared to dive deep into your technical expertise, especially with tools like PostgreSQL and any other relevant technologies. You might be asked to solve a problem on the spot, so practice articulating your thought process.
✨Emphasise Collaboration
This role requires working closely with various teams. Share experiences that highlight your ability to collaborate effectively with AI and Back End engineering teams, showcasing how you’ve contributed to successful projects.