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For Companies At a Glance
- Tasks: Design and implement data pipelines, ensuring data integrity and accessibility.
- Company: Join a forward-thinking tech company focused on data solutions.
- Benefits: Enjoy remote work flexibility and a competitive salary of GBP 70k PA.
- Why this job: Be part of a dynamic team shaping the future of data engineering.
- Qualifications: Proficient in Python, PySpark, SQL, and AWS; experience with ETL pipelines required.
- Other info: Opportunity to work with cutting-edge cloud technologies and CI/CD workflows.
The predicted salary is between 42000 - 84000 £ per year.
About the Role
The Data Engineer will play a crucial role in designing and implementing robust data pipelines, ensuring the integrity and accessibility of data across various platforms.
Required Skills
- Proficient in PySpark and AWS
- Strong experience in designing, implementing, and debugging ETL pipelines
- Expertise in Python, PySpark, and SQL
- In-depth knowledge of Spark and Airflow
- Experience in designing data pipelines using cloud-native services on AWS
- Extensive knowledge of AWS services
- Experience in deploying AWS resources using Terraform
- Hands-on experience in setting up CI/CD workflows using GitHub Actions
Preferred Skills
- Experience with additional cloud platforms
- Familiarity with data governance and compliance standards
Pay range and compensation package: GBP 70k PA REMOTE in UK
Data Engineer , Python, PySpark, and SQL, AWS employer: Athsai
Contact Detail:
Athsai Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Data Engineer , Python, PySpark, and SQL, AWS
✨Tip Number 1
Network with professionals in the data engineering field, especially those who work with AWS and PySpark. Attend meetups or webinars to connect with potential colleagues and learn about their experiences.
✨Tip Number 2
Showcase your hands-on experience by contributing to open-source projects or building your own data pipelines. This practical experience can set you apart and demonstrate your skills effectively.
✨Tip Number 3
Familiarise yourself with the latest trends and updates in AWS services and data engineering tools. Being knowledgeable about new features can give you an edge during discussions with our team.
✨Tip Number 4
Prepare for technical interviews by practising common data engineering problems and scenarios, particularly those involving ETL processes and cloud-native services. This will help you articulate your thought process clearly.
We think you need these skills to ace Data Engineer , Python, PySpark, and SQL, AWS
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights your experience with Python, PySpark, SQL, and AWS. Use specific examples of projects where you've designed and implemented ETL pipelines to demonstrate your expertise.
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 hands-on experience with Terraform and CI/CD workflows, as these are key requirements.
Showcase Relevant Projects: If you have worked on relevant projects, include them in your application. Describe your role, the technologies used, and the impact of your work, especially focusing on cloud-native services and data governance.
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 for a Data Engineer.
How to prepare for a job interview at Athsai
✨Showcase Your Technical Skills
Be prepared to discuss your experience with Python, PySpark, and SQL in detail. Bring examples of past projects where you designed and implemented ETL pipelines, and be ready to explain the challenges you faced and how you overcame them.
✨Demonstrate AWS Proficiency
Since the role requires extensive knowledge of AWS services, make sure to highlight your experience with cloud-native services. Discuss specific AWS tools you've used, such as S3, Redshift, or Lambda, and how they contributed to your data engineering projects.
✨Prepare for Scenario-Based Questions
Expect scenario-based questions that assess your problem-solving skills. For instance, you might be asked how you would handle a data pipeline failure or optimise a slow-running ETL process. Think through your approach and be ready to articulate it clearly.
✨Familiarise Yourself with CI/CD Workflows
As the role involves setting up CI/CD workflows using GitHub Actions, brush up on your knowledge of these processes. Be prepared to discuss how you have implemented CI/CD in previous roles and the benefits it brought to your projects.
