Data Engineer AWS

Data Engineer AWS

Full-Time 60000 - 84000 £ / year (est.) Home office possible
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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

As a leading employer in the tech industry, we offer our Data Engineers a dynamic and inclusive work culture that fosters innovation and collaboration. With a focus on employee growth, we provide ample opportunities for professional development and skill enhancement, particularly in cutting-edge technologies like AWS and PySpark. Our remote work model allows for flexibility, ensuring a healthy work-life balance while being part of a forward-thinking team dedicated to data excellence.
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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. This will not only help you in interviews but also show your genuine interest in the role.

✨Tip Number 2

Join online communities or forums focused on data engineering and AWS. Engaging with professionals in these spaces can provide insights into industry trends and may even lead to networking opportunities.

✨Tip Number 3

Consider working on personal projects that involve building data pipelines using PySpark and AWS. Having practical examples to discuss during interviews can significantly boost your chances of landing the job.

✨Tip Number 4

Prepare for technical interviews by practising coding challenges related to Python, SQL, and ETL processes. Being well-prepared for these challenges can set you apart from other candidates.

We think you need these skills to ace Data Engineer AWS

Proficient in PySpark
Strong experience in designing ETL pipelines
Expertise in Python
Expertise in SQL
In-depth knowledge of Spark
In-depth knowledge of Airflow
Experience in designing data pipelines using AWS services
Extensive knowledge of AWS services
Experience in deploying AWS resources using Terraform
Hands-on experience in setting up CI/CD workflows using GitHub Actions
Debugging skills for ETL pipelines
Understanding of cloud-native services

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 for this position.

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 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 PySpark, AWS, and ETL pipelines in detail. Bring examples of projects where you've successfully implemented these technologies, as this will demonstrate your hands-on expertise.

✨Understand the Company’s Data Needs

Research the company’s data architecture and any specific challenges they might face. This will allow you to tailor your answers and show how your skills can directly address their needs.

✨Prepare for Scenario-Based Questions

Expect questions that ask you to solve hypothetical problems related to data pipelines or cloud services. Practice articulating your thought process clearly, as this will showcase your problem-solving abilities.

✨Familiarise Yourself with CI/CD Practices

Since the role involves setting up CI/CD workflows using GitHub Actions, be ready to discuss your experience with these practices. Highlight any relevant projects where you’ve implemented CI/CD, as this will show your readiness for the role.

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