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- Tasks: Lead a team in developing complex data pipelines using PySpark on AWS.
- Company: Join a dynamic tech company focused on innovative data solutions.
- Benefits: Enjoy hybrid work flexibility and competitive pay for your expertise.
- Why this job: Be part of a collaborative culture that values your skills and creativity.
- Qualifications: 7+ years in data engineering with strong skills in PySpark, Glue, and AWS.
- Other info: This is a 6-month contract role, requiring office presence 2-3 days a week.
The predicted salary is between 60000 - 84000 £ per year.
Lead Data Engineer – Contract
Location: Northampton (hybrid – need to be in office 2/3 days in a week)
Duration: 6 months
Inside IR35
Job description:
* 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 experienced in designing, developing complex logic for data pipelines using pyspark in AWS along with helping/leading the team.
* He/she needs to experienced and skilled in PySpark, Glue, Python, SQL and 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.
Please send CV\’s to a.otoole@tenthrevolution if you meet each requirement
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Lead AWS Data Engineer employer: Jefferson Frank
Contact Detail:
Jefferson Frank 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 from other candidates.
✨Tip Number 3
Network with professionals in the data engineering field, particularly those who work with AWS. Engaging with others can provide insights into the role and may even lead to referrals, which can significantly boost your chances of landing the job.
✨Tip Number 4
Prepare to discuss your approach to designing ETL processes and ensuring data security. Being able to articulate your thought process and methodologies will demonstrate your expertise and understanding of the responsibilities of the role.
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. Focus on specific projects where you've designed and developed data pipelines, and quantify your achievements where possible.
Craft a Strong Cover Letter: Write a cover letter that addresses the key requirements of the job. Emphasise your leadership experience and how you have successfully led teams in developing complex data solutions using AWS services.
Showcase Relevant Skills: In your application, clearly list your technical skills such as Python, SQL, and experience with AWS services like Glue and Redshift. Provide examples of how you've used these skills in past roles.
Highlight Team Collaboration: Since the role involves collaboration with other teams, mention any relevant experiences where you've worked cross-functionally. This could include working with data analysts or business stakeholders to meet data requirements.
How to prepare for a job interview at Jefferson Frank
✨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.
✨Demonstrate Leadership Experience
Since the role requires leading a team, be ready to share instances where you've successfully guided others. Discuss your approach to mentoring and how you ensure collaboration within a team setting.
✨Understand the Business Context
Familiarise yourself with the company's business model and how data engineering supports their goals. This knowledge will help you articulate how your skills can directly benefit their operations.
✨Prepare for Scenario-Based Questions
Expect questions that assess your problem-solving abilities in real-world scenarios. Think about challenges you've faced in previous roles and how you overcame them, particularly in relation to data security and processing.
