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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 75k PA.
- Why this job: Be part of a dynamic team shaping the future of data engineering.
- Qualifications: Proficient in PySpark, AWS, Python, SQL, and ETL pipeline design.
- Other info: Ideal for tech-savvy individuals eager to innovate in cloud services.
The predicted salary is between 60000 - 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 75k PA REMOTE in UK
Data Engineer PySpark & AWS employer: Athsai
Contact Detail:
Athsai Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Data Engineer PySpark & AWS
✨Tip Number 1
Familiarise yourself with the latest features and updates in PySpark and AWS. Being able to discuss recent advancements or changes during your interview can demonstrate your passion and commitment to staying current in the field.
✨Tip Number 2
Prepare to showcase your experience with ETL pipelines by discussing specific projects you've worked on. Highlighting your problem-solving skills and how you overcame challenges in these projects can set you apart from other candidates.
✨Tip Number 3
Brush up on your knowledge of Terraform and CI/CD workflows, as these are crucial for the role. Be ready to explain how you've used these tools in past experiences, as practical examples can greatly enhance your candidacy.
✨Tip Number 4
Network with professionals in the data engineering field, especially those who work with AWS and PySpark. Engaging in relevant online communities or attending meetups can provide valuable insights and potentially lead to referrals.
We think you need these skills to ace Data Engineer PySpark & AWS
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights your experience with PySpark, AWS, and ETL pipelines. Use specific examples to demonstrate your expertise in Python, SQL, and any relevant projects you've worked on.
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 with cloud-native services and CI/CD workflows, as these are key aspects of the job.
Showcase Relevant Projects: If you have worked on projects involving Spark, Airflow, or Terraform, be sure to include these in your application. Describe your role and the impact of your contributions to demonstrate your hands-on experience.
Highlight Soft Skills: Data engineers often work in teams, so it's important to showcase your communication and collaboration skills. Mention any experiences where you successfully worked with others to achieve a common goal.
How to prepare for a job interview at Athsai
✨Showcase Your Technical Skills
Be prepared to discuss your experience with PySpark, AWS, and ETL pipelines in detail. Highlight specific projects where you've designed or implemented data pipelines, and be ready to explain the challenges you faced and how you overcame them.
✨Demonstrate Problem-Solving Abilities
Expect technical questions that assess your problem-solving skills. Practice explaining your thought process when debugging issues in data pipelines or optimising performance in Spark jobs. This will show your analytical thinking and technical expertise.
✨Familiarise Yourself with CI/CD Workflows
Since the role involves setting up CI/CD workflows using GitHub Actions, brush up on your knowledge of these processes. Be ready to discuss how you have implemented CI/CD in past projects and the benefits it brought to your workflow.
✨Understand Data Governance Standards
While not mandatory, having a grasp of data governance and compliance standards can set you apart. Be prepared to discuss how you ensure data integrity and security in your projects, as this is increasingly important in data engineering roles.
