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- Tasks: Lead data engineering projects, enhance data quality, and implement ETL pipelines.
- Company: Join a dynamic IT services company focused on data infrastructure and analytics.
- Benefits: Enjoy remote work flexibility and competitive salary of 90k GBP.
- Why this job: Be part of innovative data initiatives and collaborate with talented professionals.
- Qualifications: Experience in big data technologies, Python, Spark, and AWS is essential.
- Other info: SC clearance eligibility is required for this permanent role.
The predicted salary is between 72000 - 108000 £ per year.
We are looking for a dedicated professional with substantial experience in big data technologies to join our team. 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 is required.
- Permanent role - 90k GBP
- Responsibilities include enhancing data quality and optimizing data processes.
Lead Data Engineer Python, Spark, AWS , ETL pipelines employer: Athsai
Contact Detail:
Athsai Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Lead Data Engineer Python, Spark, AWS , ETL pipelines
✨Tip Number 1
Familiarise yourself with the specific big data technologies mentioned in the job description, such as Apache Kafka, Spark, and Airflow. Having hands-on experience or projects showcasing these tools will give you a significant edge during discussions.
✨Tip Number 2
Network with professionals in the field of data engineering, especially those who have experience with AWS services. Engaging in relevant online communities or attending meetups can help you gain insights and potentially get referrals.
✨Tip Number 3
Prepare to discuss your experience with ETL pipelines and cloud-native services in detail. Be ready to share specific examples of how you've optimised data processes in previous roles, as this will demonstrate your capability to contribute effectively.
✨Tip Number 4
If you don't currently hold SC clearance, research the process to obtain it and be prepared to discuss your eligibility. Showing initiative in understanding this requirement can set you apart from other candidates.
We think you need these skills to ace Lead Data Engineer Python, Spark, AWS , ETL pipelines
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights your experience with big data technologies, particularly focusing on ETL tools like Apache Kafka, Spark, and Airflow. Emphasise your programming skills in Python, Scala, and SQL, as well as your experience with AWS services.
Craft a Compelling Cover Letter: In your cover letter, explain why you are the perfect fit for the Lead Data Engineer role. Discuss your collaborative skills and how they will help you work effectively with stakeholders, data architects, and data scientists.
Highlight SC Clearance Eligibility: Clearly state your current SC clearance status or your eligibility to obtain it. This is crucial for the role, so make sure it's prominent in your application.
Showcase Relevant Projects: Include specific examples of projects where you implemented data pipelines using cloud-native services on AWS. This will demonstrate your hands-on experience and ability to optimise data processes.
How to prepare for a job interview at Athsai
✨Showcase Your Technical Skills
Be prepared to discuss your experience with big data technologies, especially Python, Spark, and AWS. Highlight specific projects where you've implemented ETL pipelines and how you utilised tools like Apache Kafka and Airflow.
✨Demonstrate Collaboration
Since the role involves working closely with stakeholders, data architects, and data scientists, share examples of how you've successfully collaborated in past projects. Emphasise your communication skills and ability to work in a team.
✨Understand the Importance of SC Clearance
Make sure you are familiar with the SC clearance process and be ready to discuss your eligibility. This is crucial for the role, so showing that you understand its significance will reflect well on you.
✨Prepare Questions About Data Initiatives
Have insightful questions ready about the company's data initiatives and how they plan to optimise their data processes. This shows your genuine interest in the role and helps you assess if it's the right fit for you.
