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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 £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: Experience with Terraform and CI/CD workflows is a plus.
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 AWS employer: Athsai
Contact Detail:
Athsai Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Data Engineer AWS
✨Tip Number 1
Familiarise yourself with the latest AWS services and features, especially those related to data engineering. Being able to discuss recent updates or innovations in your interview can demonstrate your passion and commitment to the field.
✨Tip Number 2
Showcase your hands-on experience with PySpark and ETL pipelines by preparing examples of past projects. Be ready to explain the challenges you faced and how you overcame them, as this will highlight your problem-solving skills.
✨Tip Number 3
Network with current Data Engineers or professionals in similar roles on platforms like LinkedIn. Engaging in discussions about best practices or trends in data engineering can provide valuable insights and potentially lead to referrals.
✨Tip Number 4
Prepare for technical interviews by practising common data engineering problems and scenarios. Focus on questions related to AWS, PySpark, and SQL, as well as designing data pipelines, to ensure you're ready to impress during the technical assessment.
We think you need these skills to ace Data Engineer 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 highlight your hands-on experience.
Proofread Your Application: Before submitting, carefully proofread your CV and cover letter for any errors. A polished application reflects your attention to detail, which is crucial for a Data Engineer role.
How to prepare for a job interview at Athsai
✨Showcase Your Technical Skills
Be prepared to discuss your proficiency in PySpark, AWS, and SQL. Bring examples of past projects where you designed and implemented ETL pipelines, as this will demonstrate your hands-on experience and technical expertise.
✨Understand the Company’s Data Needs
Research the company’s data architecture and any specific challenges they face. This will allow you to tailor your responses and show how your skills can directly address their needs.
✨Prepare for Scenario-Based Questions
Expect questions that assess your problem-solving abilities. Be ready to walk through how you would design a data pipeline or troubleshoot an issue using Spark or Airflow, showcasing your analytical thinking.
✨Demonstrate Your CI/CD Knowledge
Since the role involves setting up CI/CD workflows, be prepared to discuss your experience with GitHub Actions and Terraform. Highlight any relevant projects where you successfully deployed AWS resources and maintained code quality.
