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For Companies At a Glance
- Tasks: Design and maintain data architecture, build pipelines, and collaborate with teams.
- Company: Join a forward-thinking company focused on innovative data solutions in London.
- Benefits: Enjoy hybrid work flexibility and a supportive corporate culture.
- Why this job: Be part of a dynamic team making impactful data-driven decisions.
- Qualifications: 6+ years of experience with Python, Pyspark, SQL, and ETL processes required.
- Other info: Opportunity to work with cutting-edge cloud technologies like AWS, Azure, and GCP.
The predicted salary is between 48000 - 84000 £ per year.
About Role: 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) (, , United Kingdom) 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) (, , United Kingdom)
✨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 their experiences at companies like ours.
✨Tip Number 2
Familiarise yourself with cloud platforms such as AWS, Azure, and GCP. Consider taking online courses or certifications that focus on data engineering in these environments to demonstrate your commitment and expertise.
✨Tip Number 3
Prepare to discuss your previous projects in detail, particularly those involving ETL processes and data pipeline development. Be ready to explain the challenges you faced and how you overcame them, showcasing your problem-solving skills.
✨Tip Number 4
Stay updated on the latest trends and technologies in data engineering. Follow relevant blogs, podcasts, and forums to ensure you can speak knowledgeably about current best practices during interviews.
We think you need these skills to ace Senior Data Engineer_London_Hybrid(6+ Years) (, , United Kingdom)
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 role. Mention your experience collaborating 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, include these in your application. Highlight any documentation you've created for data pipelines or warehouses, as this demonstrates your attention to detail.
Proofread Your Application: Before submitting, carefully proofread your CV and cover letter for any errors. A polished application reflects your professionalism and attention to detail, which are crucial in a data engineering role.
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 ETL Processes
Since the role requires developing and maintaining ETL processes, brush up on your knowledge of these workflows. Be ready to discuss how you've moved data from various sources to a data warehouse, particularly in cloud environments like AWS, Azure, or GCP.
✨Collaboration is Key
Highlight your experience working with data scientists and business analysts. Prepare to discuss how you’ve collaborated to understand their data needs and how you’ve developed solutions that meet those requirements.
✨Documentation Matters
Emphasise the importance of documentation in your previous roles. Be ready to talk about how you’ve maintained documentation for data pipelines and data warehouses, and why it’s crucial for team collaboration and future scalability.
