Find a job 
Featured Companies 
Featured Universities 
For Companies At a Glance
- Tasks: Lead a team in developing complex data pipelines using PySpark on AWS.
- Company: Join a forward-thinking tech company based in Northampton, embracing innovation and collaboration.
- Benefits: Enjoy hybrid working, with flexibility to work from home 2-3 days a week.
- Why this job: Be part of a dynamic team, shaping data solutions that drive business success.
- Qualifications: 7+ years in data engineering with expertise in PySpark, AWS, SQL, and ETL processes.
- Other info: This is a 6-month contract role, inside IR35.
The predicted salary is between 54000 - 84000 £ per year.
Location: Northampton (hybrid - need to be in office 2/3 days a week)
Duration: 6 months
This will be a Tech Lead who is proficient in developing complex logic using PySpark in AWS along with helping/leading the team.
7+ years of experience in designing and developing complex logic for data pipelines using PySpark in AWS.
He/she needs to be experienced and skilled in:
- PySpark
- Glue
- Python
- SQL
- Data processing
This involves designing ETL processes, ensuring data security, and collaborating with other teams for data analysis and business requirements.
Skilled in scalable, reliable, and efficient data solutions, often using AWS services like S3, Redshift, EMR, Glue, and Kinesis.
Lead AWS Data Engineer employer: Tenth Revolution Group
Contact Detail:
Tenth Revolution Group Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Lead AWS Data Engineer
✨Tip Number 1
Make sure to showcase your leadership skills during the interview. As a Lead AWS Data Engineer, you'll be expected to guide and mentor your team, so prepare examples of how you've successfully led projects or teams in the past.
✨Tip Number 2
Brush up on your technical knowledge, especially around AWS services like S3, Redshift, and Glue. Be ready to discuss specific projects where you've implemented these technologies, as practical experience will set you apart.
✨Tip Number 3
Network with professionals in the field, particularly those who work with AWS and data engineering. Engaging with others can provide insights into the role and may even lead to referrals, which can significantly boost your chances.
✨Tip Number 4
Prepare for scenario-based questions that test your problem-solving skills in data pipeline design and ETL processes. Think through common challenges and how you would address them using PySpark and AWS tools.
We think you need these skills to ace Lead AWS Data Engineer
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights your experience with AWS, PySpark, and data engineering. Use specific examples of projects where you've designed ETL processes or led a team to demonstrate your skills.
Craft a Strong Cover Letter: Write a cover letter that addresses the key requirements mentioned in the job description. Explain how your 7+ years of experience aligns with their needs and showcase your leadership abilities in data engineering.
Highlight Relevant Skills: In your application, emphasise your proficiency in Python, SQL, and AWS services like S3, Redshift, and Glue. Mention any specific projects or achievements that illustrate your expertise in these areas.
Proofread Your Application: Before submitting, carefully proofread your CV and cover letter for any errors or typos. A polished application reflects your attention to detail, which is crucial for a Lead Data Engineer role.
How to prepare for a job interview at Tenth Revolution Group
✨Showcase Your Technical Skills
Be prepared to discuss your experience with PySpark, AWS services, and data pipeline design. Bring examples of past projects where you developed complex logic and ETL processes, as this will demonstrate your proficiency and problem-solving abilities.
✨Emphasise Leadership Experience
Since the role requires leading a team, highlight any previous leadership roles or experiences. Discuss how you've mentored others, facilitated collaboration, and driven projects to success, showcasing your ability to lead effectively.
✨Understand the Business Context
Familiarise yourself with the company's business model and how data engineering supports their goals. Be ready to discuss how your work can contribute to their objectives, particularly in terms of data analysis and security.
✨Prepare for Scenario-Based Questions
Expect questions that assess your problem-solving skills in real-world scenarios. Practice articulating your thought process when faced with challenges related to data processing, security, and team collaboration, as this will reflect your critical thinking and adaptability.
