Lead Data Engineer
Lead AWS Data Engineer
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.
Private healthcare & medical cashback plan.
Monthly gym membership contribution.
Annual personal development allowance.
Regular team socials in a collaborative environment.
Reference: 2937673590
Lead Data Engineer

Posted on Apr 24, 2025 by Amber Resourcing Ltd
Lead AWS Data Engineer
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.
Private healthcare & medical cashback plan.
Monthly gym membership contribution.
Annual personal development allowance.
Regular team socials in a collaborative environment.
Reference: 2937673590

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