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For Companies At a Glance
- Tasks: Design and implement data pipelines to ensure data integrity and accessibility.
- Company: Join Athsai, a dynamic company at the forefront of data engineering.
- Benefits: Enjoy flexible working options and a collaborative team environment.
- Why this job: Be part of an innovative team making a real impact in data management.
- Qualifications: Proficient in Python, PySpark, SQL, and AWS; experience with ETL pipelines required.
- Other info: EU work permit is necessary; located in South West London.
The predicted salary is between 36000 - 60000 £ 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
Data Engineer , Python, PySpark, and SQL, AWS employer: JR United Kingdom
Contact Detail:
JR United Kingdom 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 local meetups or online webinars to connect with potential colleagues and learn about the latest industry trends.
✨Tip Number 2
Showcase your hands-on experience by contributing to open-source projects or building your own data pipelines using AWS services. This practical experience can set you apart from other candidates.
✨Tip Number 3
Familiarise yourself with the specific tools and technologies mentioned in the job description, such as Terraform and GitHub Actions. Being able to discuss these in detail during an interview will demonstrate your readiness for the role.
✨Tip Number 4
Prepare for technical interviews by practising coding challenges related to Python, SQL, and data pipeline design. Websites like LeetCode or HackerRank can be great resources to sharpen your skills.
We think you need these skills to ace Data Engineer , Python, PySpark, and SQL, AWS
Some tips for your application 🫡
Understand the Role: Before applying, make sure you fully understand the responsibilities of a Data Engineer. Familiarise yourself with the required skills such as PySpark, AWS, and SQL, and think about how your experience aligns with these.
Tailor Your CV: Customise your CV to highlight your relevant experience in data engineering, particularly with Python, PySpark, and AWS. Use specific examples of projects where you've designed or implemented ETL pipelines.
Craft a Compelling Cover Letter: Write a cover letter that showcases your passion for data engineering and your understanding of the role. Mention your hands-on experience with AWS services and any familiarity with CI/CD workflows, as these are key aspects of the job.
Proofread Your Application: Before submitting, carefully proofread your application materials. Check for any spelling or grammatical errors, and ensure that all technical terms are used correctly. A polished application reflects your attention to detail.
How to prepare for a job interview at JR United Kingdom
✨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 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 any relevant experience. Discuss specific AWS tools you've used, such as S3, Redshift, or Lambda, and how they contributed to your data engineering projects.
✨Understand Data Governance
Familiarise yourself with data governance and compliance standards, as these are important in the role. Be ready to discuss how you ensure data integrity and security in your projects, and any frameworks or practices you follow.
✨Prepare for Problem-Solving Questions
Expect technical questions that assess your problem-solving skills. Practice explaining your thought process when debugging ETL pipelines or optimising data workflows, as this will demonstrate your analytical abilities and approach to challenges.
