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For Companies At a Glance
- Tasks: Lead a team to design and optimise AWS data solutions.
- Company: Join a dynamic FinTech company revolutionising regulatory technology.
- Benefits: Enjoy hybrid work, 25 days holiday, private healthcare, and gym contributions.
- Why this job: Be part of a collaborative culture that values innovation and personal growth.
- Qualifications: 7+ years in data engineering with strong AWS and leadership experience required.
- Other info: Regular team socials and an annual personal development allowance included.
The predicted salary is between 72000 - 84000 £ per year.
A 200-employee data and technology company specialising in Regulatory Technology (RegTech) are looking for a Lead AWS Data Engineer. They develop products that enhance data quality and help financial institutions navigate regulatory compliance.
The Role
The Lead Data Engineer will provide technical leadership to a small team of Data Engineers (onshore & offshore), driving the design, implementation, and optimisation of scalable data solutions in AWS.
Key Responsibilities
- Lead and mentor a team of onshore and offshore Data Engineers, driving technical growth and ensuring effective collaboration.
- Design, develop, and optimise scalable data pipelines and infrastructure using AWS (Glue, Athena, Redshift, Kinesis, Step Functions, Lake Formation).
- Utilise PySpark for distributed data processing, ETL, SQL querying, and real-time data streaming.
- Architect and implement robust data solutions for analytics, reporting, machine learning, and data science initiatives.
- Establish and enforce best practices in data engineering, coding standards, and architecture guidelines.
- Manage team tasks and delivery using Agile methodologies, collaborating closely with product owners and scrum masters.
Skills and Experience
- 2+ years of leadership experience in data engineering, including mentoring and team management.
- 7+ years of hands-on experience in data engineering and ETL architecture.
- Deep expertise in AWS Data Services, including Glue, Athena, Redshift, Kinesis, Step Functions, and Lake Formation.
- Strong programming skills in Python and PySpark for data processing and automation.
- Extensive SQL experience (Spark-SQL, MySQL, Presto SQL) and familiarity with NoSQL databases (DynamoDB, MongoDB, etc.).
- Proficiency in Infrastructure-as-Code (Terraform, CloudFormation) for automating AWS data workflows.
- Experience designing, implementing, and optimising ETL pipelines, including real-time data processing and streaming architectures.
25 days holiday + bank holidays + birthday off. Private healthcare & medical cashback plan. Monthly gym membership contribution. Annual personal development allowance. Regular team socials in a collaborative environment.
Lead AWS Data Engineer employer: F5 Consultants
Contact Detail:
F5 Consultants Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Lead AWS Data Engineer
✨Tip Number 1
Familiarise yourself with the specific AWS services mentioned in the job description, such as Glue, Athena, and Redshift. Having hands-on experience or projects that showcase your skills with these tools will make you stand out during discussions.
✨Tip Number 2
Highlight your leadership experience by preparing examples of how you've successfully mentored teams or led projects in the past. Be ready to discuss your approach to fostering collaboration and technical growth within a team.
✨Tip Number 3
Brush up on Agile methodologies, as this role involves managing tasks and delivery using Agile practices. Being able to articulate your experience with Agile frameworks will demonstrate your fit for the team's workflow.
✨Tip Number 4
Prepare to discuss your experience with Infrastructure-as-Code tools like Terraform or CloudFormation. Providing concrete examples of how you've automated AWS workflows will show your technical depth and problem-solving abilities.
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 relevant experience in data engineering, particularly with AWS services like Glue, Athena, and Redshift. Emphasise your leadership skills and any mentoring experience you've had.
Craft a Compelling Cover Letter: In your cover letter, explain why you're passionate about the FinTech/RegTech industry and how your background aligns with the company's mission. Mention specific projects where you've led teams or implemented scalable data solutions.
Showcase Technical Skills: Clearly outline your technical skills related to AWS Data Services, PySpark, and SQL in your application. Provide examples of how you've used these technologies to solve complex problems or improve processes.
Highlight Team Collaboration: Since the role involves managing a team, include examples of how you've successfully collaborated with others in an Agile environment. Discuss your experience working with product owners and scrum masters to deliver projects.
How to prepare for a job interview at F5 Consultants
✨Showcase Your Leadership Skills
As a Lead AWS Data Engineer, you'll be expected to mentor and guide a team. Be prepared to discuss your previous leadership experiences, how you've fostered collaboration, and any specific examples of how you've helped team members grow.
✨Demonstrate Technical Expertise
Make sure you can talk in-depth about your experience with AWS services like Glue, Athena, and Redshift. Prepare to explain how you've used these tools in past projects, focusing on the design and optimisation of data pipelines.
✨Prepare for Scenario-Based Questions
Expect questions that assess your problem-solving skills in real-world scenarios. Think about challenges you've faced in data engineering, particularly with ETL processes or real-time data streaming, and how you overcame them.
✨Familiarise Yourself with Agile Methodologies
Since the role involves managing tasks using Agile practices, be ready to discuss your experience with Agile frameworks. Highlight how you've collaborated with product owners and scrum masters to deliver successful projects.
