Find a job 
Featured Companies 
Featured Universities 
For Companies At a Glance
- Tasks: Design and maintain data architecture, build pipelines, and collaborate with teams.
- Company: Join a dynamic tech company focused on innovative data solutions.
- Benefits: Enjoy hybrid work flexibility and opportunities for professional growth.
- Why this job: Be part of a cutting-edge team making impactful data-driven decisions.
- Qualifications: 6+ years of experience with Python, Pyspark, SQL, and ETL processes required.
- Other info: This is a permanent position based in London.
The predicted salary is between 48000 - 72000 £ per year.
As a Data Engineer, you will play a crucial role in designing, developing, and maintaining data architecture and infrastructure. The successful candidate should possess a strong foundation in Python, Pyspark, SQL, and ETL processes, with a demonstrated ability to implement solutions in a cloud environment.
Mandatory Skills:
- Design, build, maintain data pipelines using Python, Pyspark and SQL
- Develop and maintain ETL processes to move data from various data sources to our data warehouse on AWS/AZURE/GCP
- Collaborate with data scientists, business analysts to understand their data needs & develop solutions that meet their requirements
- Develop & maintain data models and data dictionaries for our data warehouse
- Develop & maintain documentation for our data pipelines and data warehouse
- Continuously improve the performance and scalability of our data solutions
Qualifications:
- Minimum 6+ years of Total experience
- At least 4+ years of Hands on Experience using The Mandatory skills - Python, Pyspark, SQL
Senior Data Engineer_London_Hybrid(6+ Years) employer: Databuzz Ltd
Contact Detail:
Databuzz Ltd Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Senior Data Engineer_London_Hybrid(6+ Years)
✨Tip Number 1
Network with professionals in the data engineering field, especially those who work with Python, Pyspark, and SQL. Attend meetups or webinars to connect with potential colleagues and learn about the latest trends in data architecture.
✨Tip Number 2
Showcase your experience with cloud platforms like AWS, Azure, or GCP by discussing relevant projects during interviews. Be prepared to explain how you've implemented ETL processes and maintained data pipelines in these environments.
✨Tip Number 3
Familiarise yourself with the specific data needs of our company by researching our products and services. This will help you tailor your discussions and demonstrate how your skills can directly benefit our team.
✨Tip Number 4
Prepare to discuss your approach to documentation and maintaining data models. Highlight any tools or methodologies you've used to ensure clarity and efficiency in your data solutions, as this is crucial for collaboration with data scientists and analysts.
We think you need these skills to ace Senior Data Engineer_London_Hybrid(6+ Years)
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights your experience with Python, Pyspark, SQL, and ETL processes. Use specific examples of projects where you've designed and maintained data pipelines, especially in cloud environments like AWS, Azure, or GCP.
Craft a Compelling Cover Letter: In your cover letter, explain why you're passionate about data engineering and how your skills align with the company's needs. Mention your collaborative experiences with data scientists and business analysts to showcase your teamwork abilities.
Showcase Relevant Projects: If you have worked on significant projects that involved developing data models or improving data solutions, be sure to include these in your application. Highlight any documentation you created for data pipelines and warehouses.
Proofread Your Application: Before submitting, carefully proofread your application for any spelling or grammatical errors. A polished application reflects your attention to detail, which is crucial in data engineering roles.
How to prepare for a job interview at Databuzz Ltd
✨Showcase Your Technical Skills
Be prepared to discuss your experience with Python, Pyspark, and SQL in detail. Bring examples of projects where you've designed and built data pipelines, and be ready to explain the challenges you faced and how you overcame them.
✨Understand the Cloud Environment
Since the role involves working with AWS, Azure, or GCP, make sure you have a solid understanding of these platforms. Familiarise yourself with their data services and be ready to discuss how you've used them in previous roles.
✨Collaboration is Key
Highlight your experience working with data scientists and business analysts. Be prepared to discuss how you gather requirements and translate them into technical solutions, as collaboration is crucial in this role.
✨Documentation Matters
Emphasise the importance of maintaining documentation for data pipelines and data models. Be ready to share how you approach documentation and why it’s essential for team collaboration and future scalability.
