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- Tasks: Build and enhance data flows while applying software engineering and DevOps principles.
- Company: Leading UK technology firm with a focus on innovation and collaboration.
- Benefits: Flexible hybrid working, emphasis on well-being, and a diverse workplace.
- Why this job: Join a dynamic team and make a real impact on data-driven projects.
- Qualifications: Strong skills in SQL and Python, with a knack for collaboration.
- Other info: Great opportunities for personal growth and career advancement.
The predicted salary is between 48000 - 72000 £ per year.
A leading technology firm in the UK is looking for a Data Engineer to build and improve data flows, applying software engineering and DevOps principles. The role demands collaboration with clients to understand their data requirements and involves communicating across various teams. Strong technical skills in SQL and Python are essential. The company promotes a flexible working environment with emphasis on hybrid working, well-being, and diversity among its personnel.
Senior Data Engineer: Lead Data Flows & Platforms employer: BAE Systems.
Contact Detail:
BAE Systems. Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Senior Data Engineer: Lead Data Flows & Platforms
✨Tip Number 1
Network like a pro! Reach out to your connections in the tech industry, especially those who work in data engineering. 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 in SQL and Python. 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 explaining complex data flows in simple terms, as communication is key in this role.
✨Tip Number 4
Don’t forget to apply through our website! We’ve got loads of opportunities that might just be the perfect fit for you. Plus, it’s a great way to show your interest in joining our diverse and flexible team.
We think you need these skills to ace Senior Data Engineer: Lead Data Flows & Platforms
Some tips for your application 🫡
Show Off Your Skills: Make sure to highlight your technical skills in SQL and Python right from the start. We want to see how you can apply these skills to build and improve data flows, so don’t hold back!
Tailor Your Application: Take a moment to customise your application for this role. Mention how your experience aligns with the job description, especially around software engineering and DevOps principles. It’ll make a big difference!
Communicate Clearly: Since collaboration is key, ensure your written communication is clear and concise. We love candidates who can articulate their thoughts well, especially when it comes to understanding data requirements.
Apply Through Our Website: Don’t forget to submit your application through our website! It’s the best way for us to keep track of your application and ensures you’re considered for this exciting opportunity.
How to prepare for a job interview at BAE Systems.
✨Know Your Tech Inside Out
Make sure you brush up on your SQL and Python skills before the interview. Be ready to discuss specific projects where you've applied these technologies, as well as any challenges you faced and how you overcame them.
✨Understand the Company Culture
Since the company values flexibility, well-being, and diversity, think about how your own values align with theirs. Prepare examples that showcase your adaptability and how you’ve contributed to a diverse team environment in the past.
✨Prepare for Collaborative Scenarios
As the role involves working closely with clients and various teams, be ready to discuss your experience in collaboration. Think of instances where you successfully gathered requirements or communicated complex data concepts to non-technical stakeholders.
✨Ask Insightful Questions
Show your interest in the role by preparing thoughtful questions about their data flows and platforms. Inquire about the tools they use, their approach to DevOps, and how they measure success in their data engineering projects.
