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- Tasks: Build and optimise data pipelines to drive insights for decision-makers.
- Company: Global digital media company with a focus on innovation.
- Benefits: Competitive salary, flexible working options, and opportunities for growth.
- Why this job: Join a dynamic team and make an impact through data-driven decisions.
- Qualifications: Strong Python/PySpark skills and experience with GCP or AWS.
- Other info: Collaborative environment with exciting projects and career advancement.
The predicted salary is between 30000 - 50000 £ per year.
A global digital media company is seeking a Data Engineer to enhance data pipelines and infrastructure. This role focuses on optimizing data flows and insights that empower decision-makers across the business.
The ideal candidate should have strong Python and/or PySpark skills with experience in cloud technologies like GCP and AWS. The position involves collaboration with various teams to support strategic projects while maintaining data quality and performance.
Data Engineer: Build Scalable Pipelines & Insights employer: Data Idols
Contact Detail:
Data Idols Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Data Engineer: Build Scalable Pipelines & Insights
✨Tip Number 1
Network like a pro! Reach out to folks in the industry, especially those working at companies you're eyeing. A friendly chat can open doors and give you insider info on job openings.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your data pipelines and projects. This is your chance to demonstrate your Python and PySpark expertise, so make it shine!
✨Tip Number 3
Prepare for interviews by brushing up on cloud technologies like GCP and AWS. We all know that being well-versed in these tools can set you apart from the competition.
✨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 Data Engineer: Build Scalable Pipelines & Insights
Some tips for your application 🫡
Show Off Your Skills: Make sure to highlight your Python and PySpark skills in your application. We want to see how you can optimise data flows and enhance our infrastructure, so don’t hold back on showcasing your technical prowess!
Tailor Your Application: Take a moment to customise your application for this role. Mention your experience with cloud technologies like GCP and AWS, and how you've used them to support strategic projects. This will help us see how you fit into our team.
Collaborate in Your Writing: Since this role involves working with various teams, it’s a good idea to mention any collaborative projects you've been part of. We love seeing how you’ve worked with others to maintain data quality and performance.
Apply Through Our Website: Don’t forget to apply through our website! It’s the best way for us to receive your application and ensures you’re considered for the Data Engineer position. We can’t wait to see what you bring to the table!
How to prepare for a job interview at Data Idols
✨Know Your Tech Inside Out
Make sure you brush up on your Python and PySpark skills before the interview. Be ready to discuss specific projects where you've used these technologies, and think about how you optimised data flows in those instances.
✨Familiarise Yourself with Cloud Platforms
Since the role involves GCP and AWS, it’s crucial to understand their functionalities. Prepare to talk about your experience with these platforms, including any challenges you faced and how you overcame them.
✨Collaboration is Key
This position requires working with various teams, so be prepared to share examples of how you've successfully collaborated in the past. Highlight your communication skills and how you ensure everyone is on the same page.
✨Data Quality Matters
Be ready to discuss how you maintain data quality and performance in your projects. Think of specific metrics or methods you've used to ensure that the data pipelines you built are reliable and efficient.
