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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.
- Benefits: Enjoy hybrid work flexibility and opportunities for professional growth.
- Why this job: Be part of a dynamic team making impactful data-driven decisions.
- Qualifications: 6+ years of experience with Python, Pyspark, and SQL required.
- Other info: This is a permanent position based in London.
The predicted salary is between 48000 - 84000 £ 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 and business analysts to understand their data needs and develop solutions that meet their requirements
- Develop and maintain data models and data dictionaries for our data warehouse
- Develop and 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
Familiarise yourself with the latest trends and technologies in data engineering, especially around cloud platforms like AWS, Azure, and GCP. This knowledge will not only help you during interviews but also demonstrate your commitment to staying current in the field.
✨Tip Number 2
Network with professionals in the data engineering space, particularly those who work with Python, Pyspark, and SQL. Attend meetups or webinars to connect with potential colleagues and learn about their experiences, which can provide valuable insights for your application.
✨Tip Number 3
Prepare to discuss specific projects where you've designed and maintained data pipelines. Be ready to explain your thought process, the challenges you faced, and how you overcame them, as this will showcase your problem-solving skills and hands-on experience.
✨Tip Number 4
Demonstrate your collaborative skills by preparing examples of how you've worked with data scientists and business analysts in the past. Highlight your ability to understand their data needs and how you developed solutions that met those requirements.
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 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 created for data pipelines and 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 involves developing and maintaining ETL processes, make sure you can articulate your understanding of these processes. Discuss specific tools and techniques you've used to move data from various sources to a data warehouse.
✨Collaboration is Key
Highlight your experience working with data scientists and business analysts. Be ready to share examples of how you've collaborated to understand their data needs and developed solutions that met those requirements.
✨Continuous Improvement Mindset
Demonstrate your commitment to improving data solutions. Discuss any initiatives you've taken to enhance performance and scalability in your previous roles, and be prepared to suggest how you could apply this mindset at the new company.
