At a Glance
- Tasks: Architect and own data pipelines, ensuring reliable and scalable data infrastructure.
- Company: Join a forward-thinking company at the forefront of AI and data engineering.
- Benefits: Competitive salary, flexible working hours, and opportunities for professional growth.
- Other info: Dynamic team environment with a focus on innovation and responsible AI practices.
- Why this job: Make a real impact by enabling stakeholders to harness AI for their analysis.
- Qualifications: Experience in data engineering and a passion for AI and analytics.
The predicted salary is between 70000 - 90000 € per year.
You will join our Data team as owner of our data infrastructure with an opportunity to architect and own the data pipelines, platforms and practices that will power our Data Platform. A key part of this role is improving and defining how stakeholders can use AI to self-serve their own analysis. You’ll sit at the intersection of data engineering and applied AI, working closely with analytics engineers and analysts. You will define the standards and systems that allow the data team and stakeholders to self-serve analysis using AI as a base— ensuring the data foundation is reliable, scalable and ready to fuel our AI and LLM capabilities.
What You’ll Do
- Build and maintain scalable data pipelines to ingest, transform and integrate data from multiple sources, defining best practice along the way.
- Implement robust monitoring for data ingestion jobs and take swift corrective action when issues arise.
- Work with business stakeholders to translate requirements into efficient pipeline architectures, database structures and optimised data models.
- Partner with analytics engineers to ensure clean, accessible data is available to analysts across the organisation.
- Champion responsible AI principles in the design and deployment of data systems that underpin our LLM and RAG implementations.
- Lead on development standards, version control, quality control, deployment and change management processes.
- Monitor, measure and maintain high data quality standards across all data products and pipelines.
Who You Are
Lead Data Engineer employer: Manual
As a Lead Data Engineer at our company, you will thrive in a dynamic and innovative work culture that prioritises collaboration and continuous learning. We offer competitive benefits, including professional development opportunities and a commitment to responsible AI practices, all within a vibrant location that fosters creativity and growth. Join us to make a meaningful impact on our data infrastructure while enjoying a supportive environment that values your contributions.
StudySmarter Expert Advice🤫
We think this is how you could land Lead Data Engineer
✨Tip Number 1
Network like a pro! Reach out to folks in the data engineering and AI space on LinkedIn or at meetups. We can’t stress enough how valuable personal connections can be when it comes to landing that dream job.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your data pipelines and any AI projects you've worked on. This is your chance to demonstrate your expertise and make a lasting impression on potential employers.
✨Tip Number 3
Prepare for those interviews! Brush up on your technical knowledge and be ready to discuss how you’ve tackled challenges in data engineering. We recommend practising common interview questions with a friend or using mock interview platforms.
✨Tip Number 4
Don’t forget to apply through our website! It’s the best way to ensure your application gets seen by the right people. Plus, we love seeing candidates who are genuinely interested in joining our team!
We think you need these skills to ace Lead Data Engineer
Some tips for your application 🫡
Show Your Passion for Data:When writing your application, let us see your enthusiasm for data engineering and AI. Share any personal projects or experiences that highlight your skills and passion for building scalable data pipelines and working with analytics.
Tailor Your Application:Make sure to customise your application to reflect the specific requirements of the Lead Data Engineer role. Highlight your experience with data infrastructure, monitoring, and collaboration with stakeholders to show us you’re the perfect fit.
Be Clear and Concise:We appreciate clarity! Use straightforward language and avoid jargon where possible. Make it easy for us to understand your experience and how it relates to the responsibilities outlined in the job description.
Apply Through Our Website:Don’t forget to submit your application through our website! It’s the best way for us to receive your details and ensures you’re considered for the role. Plus, it shows us you’re keen on joining the StudySmarter team!
How to prepare for a job interview at Manual
✨Know Your Data Inside Out
Make sure you’re well-versed in data engineering concepts and practices. Brush up on your knowledge of data pipelines, database structures, and AI applications. Being able to discuss specific examples from your past experience will show that you can hit the ground running.
✨Showcase Your Problem-Solving Skills
Prepare to discuss how you've tackled challenges in previous roles, especially around data quality and pipeline issues. Think of specific instances where you implemented monitoring or corrective actions, as this will demonstrate your proactive approach to maintaining high standards.
✨Understand Stakeholder Needs
Familiarise yourself with how different stakeholders use data for analysis. Be ready to explain how you would translate their requirements into efficient data architectures. This shows that you can bridge the gap between technical and non-technical teams, which is crucial for this role.
✨Champion Responsible AI
Be prepared to discuss your views on responsible AI principles and how they apply to data systems. Highlight any experience you have in implementing ethical AI practices, as this aligns with the company’s values and demonstrates your commitment to responsible data usage.
