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- Tasks: Design and implement ETL pipelines while collaborating with data teams.
- Company: Join a forward-thinking company focused on enhancing data quality and architecture.
- Benefits: Enjoy remote work flexibility and the chance to work with cutting-edge technologies.
- Why this job: Make a real impact on customer data initiatives and grow your skills in big data.
- Qualifications: Experience with ETL tools, AWS services, and programming in Python, Scala, and SQL required.
- Other info: SC clearance eligibility is necessary for this role.
The predicted salary is between 43200 - 72000 £ per year.
- Location: Scotland remote
- Start Date: January
Job Description:
We are looking for a dedicated professional with substantial hands-on experience in big data technologies to join our team.
In this role, you will have the opportunity to design, implement, and debug effective ETL pipelines, contributing to our overall data architecture.
Your collaborative skills will be key as you work alongside stakeholders, data architects, and data scientists to enhance data quality across our projects.
We value your expertise in ETL tools, including Apache Kafka, Spark, and Airflow, and your strong programming skills in Python, Scala, and SQL will further enrich our capabilities. Additionally, your experience in implementing data pipelines utilizing cloud-native services on AWS will be invaluable.
Your comprehensive knowledge of AWS services such as API Gateway, Lambda, Redshift, Glue, and CloudWatch will enable us to optimize our data processes.
We look forward to your contributions in making meaningful advancements in our Customers data initiatives!
Eligibility for SC clearance or an existing SC clearance is required for this role.
Data Engineer AWS services / ETL pipelines employer: Athsai
Contact Detail:
Athsai Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Data Engineer AWS services / ETL pipelines
✨Tip Number 1
Make sure to showcase your hands-on experience with big data technologies during networking opportunities. Engage in discussions about ETL pipelines and AWS services, as this will help you connect with professionals who can refer you to our team.
✨Tip Number 2
Join online communities or forums focused on data engineering and AWS. Participating in these groups can provide insights into industry trends and may lead to job referrals or recommendations for positions like the one we have available.
✨Tip Number 3
Consider contributing to open-source projects that utilize Apache Kafka, Spark, or Airflow. This not only enhances your skills but also demonstrates your commitment to the field, making you a more attractive candidate for our Data Engineer position.
✨Tip Number 4
If you have existing SC clearance, highlight it in conversations and networking events. If not, familiarize yourself with the process of obtaining it, as this could be a significant advantage when applying for our role.
We think you need these skills to ace Data Engineer AWS services / ETL pipelines
Some tips for your application 🫡
Highlight Relevant Experience: Make sure to emphasize your hands-on experience with big data technologies and ETL tools like Apache Kafka, Spark, and Airflow. Provide specific examples of projects where you successfully implemented these technologies.
Showcase Programming Skills: Clearly outline your programming skills in Python, Scala, and SQL. Mention any relevant projects or contributions that demonstrate your proficiency in these languages.
Detail AWS Knowledge: Discuss your comprehensive knowledge of AWS services such as API Gateway, Lambda, Redshift, Glue, and CloudWatch. Explain how you have utilized these services to optimize data processes in previous roles.
Mention SC Clearance: If you have eligibility for SC clearance or already possess it, make sure to mention this in your application. This is a key requirement for the role and can strengthen your candidacy.
How to prepare for a job interview at Athsai
✨Showcase Your ETL Expertise
Be prepared to discuss your hands-on experience with ETL tools like Apache Kafka, Spark, and Airflow. Share specific examples of how you've designed and implemented ETL pipelines in previous roles.
✨Demonstrate Cloud Knowledge
Highlight your experience with AWS services such as API Gateway, Lambda, Redshift, Glue, and CloudWatch. Discuss how you've utilized these services to optimize data processes and improve data quality.
✨Collaborative Mindset
Emphasize your collaborative skills by sharing experiences where you worked alongside stakeholders, data architects, or data scientists. Show that you value teamwork and can effectively communicate technical concepts to non-technical team members.
✨Prepare for Technical Questions
Expect technical questions related to big data technologies and programming languages like Python, Scala, and SQL. Brush up on your coding skills and be ready to solve problems on the spot, demonstrating your analytical thinking.
