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- Tasks: Lead the design of scalable data pipelines and mentor junior engineers.
- Company: ESP Engineered, a dynamic tech company in Greater London.
- Benefits: Innovative work environment with opportunities for continuous learning.
- Other info: Collaborate with cross-functional teams in a fast-paced setting.
- Why this job: Join a team driving AI-driven projects and make a significant impact.
- Qualifications: 7+ years in data engineering and proficiency in Apache Spark and Azure Data Factory.
The predicted salary is between 80000 - 105000 £ per year.
ESP Engineered is seeking a highly skilled Lead Data Engineer to join our team in Greater London. The role involves leading the design and development of scalable data pipelines, collaborating with cross-functional teams, and mentoring junior engineers.
Ideal candidates will have over 7 years of experience in data engineering, proficiency in tools like Apache Spark and Azure Data Factory, and familiarity with AI and machine learning concepts. This role offers a dynamic work environment, promoting innovation and continuous learning.
Senior Data Engineering Lead - AI-Driven Pipelines employer: ESP Engineered
Contact Detail:
ESP Engineered Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Senior Data Engineering Lead - AI-Driven Pipelines
✨Tip Number 1
Network like a pro! Reach out to your connections in the data engineering field, especially those who work with AI-driven pipelines. A friendly chat can lead to insider info about job openings or even referrals.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your projects, especially those involving Apache Spark and Azure Data Factory. This will give potential employers a taste of what you can bring to the table.
✨Tip Number 3
Prepare for interviews by brushing up on your technical knowledge and soft skills. Practice explaining complex concepts in simple terms, as you'll need to collaborate with cross-functional teams.
✨Tip Number 4
Don't forget to apply through our website! We love seeing candidates who are proactive and engaged. Plus, it gives us a chance to see your enthusiasm for joining our innovative team.
We think you need these skills to ace Senior Data Engineering Lead - AI-Driven Pipelines
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights your experience in data engineering, especially with tools like Apache Spark and Azure Data Factory. We want to see how your skills align with the role, so don’t be shy about showcasing relevant projects!
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 your experience makes you the perfect fit for our team. We love seeing enthusiasm and a bit of personality!
Showcase Your Leadership Skills: Since this is a lead position, make sure to highlight any mentoring or leadership experience you have. We’re looking for someone who can guide junior engineers and collaborate effectively with cross-functional teams.
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’re considered for the role. Plus, it’s super easy – just a few clicks and you’re done!
How to prepare for a job interview at ESP Engineered
✨Know Your Tech Inside Out
Make sure you brush up on your knowledge of Apache Spark and Azure Data Factory. Be ready to discuss specific projects where you've used these tools, as well as any challenges you faced and how you overcame them.
✨Showcase Your Leadership Skills
Since this role involves mentoring junior engineers, prepare examples of how you've led teams or projects in the past. Highlight your approach to collaboration and how you foster a positive team environment.
✨Understand AI and Machine Learning Concepts
Familiarise yourself with the latest trends in AI and machine learning, especially as they relate to data engineering. Be prepared to discuss how you can integrate these concepts into scalable data pipelines.
✨Ask Insightful Questions
Prepare thoughtful questions about the company's data strategy and future projects. This shows your genuine interest in the role and helps you assess if the company aligns with your career goals.