Lead AWS Data Engineer

JR United Kingdom; London; Hybrid; GBP 90,000 - 120,000; Full time

Job summary

An established industry player in the FinTech sector is seeking a Lead AWS Data Engineer to join their dynamic team. This role involves providing technical leadership to a talented group of Data Engineers, focusing on the design and implementation of scalable data solutions in AWS. The ideal candidate will have extensive experience with AWS Data Services and a strong programming background in Python and PySpark. With a collaborative environment and a commitment to personal development, this opportunity promises to be both rewarding and impactful for the right individual.

Benefits

25 days holiday + bank holidays + birthday off

Annual personal development allowance

Regular team socials

Qualifications

• 2+ years of leadership experience in data engineering.
• 7+ years of hands-on experience in data engineering and ETL architecture.

Responsibilities

• Lead and mentor a team of Data Engineers, driving technical growth.
• Design and optimise scalable data pipelines using AWS services.

Skills

Leadership in Data Engineering

AWS Data Services

Python Programming

PySpark

SQL (Spark-SQL, MySQL, Presto SQL)

NoSQL Databases (DynamoDB, MongoDB)

Infrastructure-as-Code (Terraform, CloudFormation)

Tools

AWS Glue

AWS Athena

AWS Redshift

AWS Kinesis

AWS Step Functions

AWS Lake Formation

Job description

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? City of London (Hybrid: Around 2-3 office days per week)

? Salary: Up to £120,000

? Industry: FinTech / RegTech

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.

? Annual personal development allowance.

? Regular team socials in a collaborative environment.