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For Companies At a Glance
- Tasks: Lead the development of scalable data solutions and support various teams.
- Company: A leading entertainment tech company redefining live experiences.
- Benefits: Remote work, competitive salary, and opportunities for innovation.
- Why this job: Join us to drive innovation in data products and shape the future of entertainment.
- Qualifications: 6+ years in data engineering with expertise in Python, SQL, and AWS.
The predicted salary is between 43200 - 72000 £ per year.
A leading entertainment technology company is seeking a Staff Data Engineer in the UK timezone to enhance its data platforms. You will provide hands-on technical leadership, build scalable data solutions, and support multiple teams.
The ideal candidate has over 6 years of experience in data engineering, with strong skills in Python, SQL, and AWS technologies.
Join us to help redefine live entertainment and drive innovation in our data products.
Staff Data Engineer - Remote, Scale Data Platform in London employer: Dice
Contact Detail:
Dice Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Staff Data Engineer - Remote, Scale Data Platform in London
✨Tip Number 1
Network like a pro! Reach out to folks in the industry, attend meetups, and connect with potential colleagues on LinkedIn. You never know who might have the inside scoop on job openings or can put in a good word for you.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your data engineering projects, especially those using Python, SQL, and AWS. This will give you an edge and demonstrate your hands-on experience to potential employers.
✨Tip Number 3
Prepare for technical interviews by brushing up on your coding skills and understanding data architecture. Practice common data engineering problems and be ready to discuss your past projects in detail.
✨Tip Number 4
Don’t forget to apply through our website! We’re always on the lookout for talented individuals like you. Keep an eye on our job listings and make sure your application stands out by tailoring it to the role.
We think you need these skills to ace Staff Data Engineer - Remote, Scale Data Platform in London
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights your experience in data engineering, especially with Python, SQL, and AWS. We want to see how your skills align with what we're looking for, 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 you can contribute to our mission of redefining live entertainment. Keep it engaging and personal!
Showcase Your Leadership Skills: Since we’re looking for someone to provide hands-on technical leadership, make sure to mention any experience you have leading teams or projects. We love seeing how you’ve driven innovation in your previous roles!
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 follow the prompts!
How to prepare for a job interview at Dice
✨Know Your Tech Inside Out
Make sure you brush up on your Python, SQL, and AWS skills before the interview. Be ready to discuss specific projects where you've used these technologies, as well as any challenges you faced and how you overcame them.
✨Showcase Your Leadership Skills
As a Staff Data Engineer, you'll be expected to provide technical leadership. Prepare examples of how you've led teams or projects in the past, focusing on your ability to mentor others and drive successful outcomes.
✨Understand the Company’s Vision
Research the entertainment technology company and its data products. Be prepared to discuss how your experience aligns with their goals and how you can contribute to redefining live entertainment through innovative data solutions.
✨Prepare for Scenario-Based Questions
Expect questions that assess your problem-solving abilities. Think about scenarios where you've had to build scalable data solutions or support multiple teams, and be ready to explain your thought process and decision-making.
