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Senior Data Engineer - AWS / Machine Learning

Interquest
Posted 2 days ago, valid for 2 days
Location

London, Greater London EC1R 0WX

Salary

£600 - £35 per day

Contract type

Full Time

In order to submit this application, a Reed account will be created for you. As such, in addition to applying for this job, you will be signed up to all Reed’s services as part of the process. By submitting this application, you agree to Reed’s Terms and Conditions and acknowledge that your personal data will be transferred to Reed and processed by them in accordance with their Privacy Policy.

Sonic Summary

info
  • This contract opportunity is for a Senior AWS Machine Learning Data Engineer located in London, with a duration of 6 months and a potential extension.
  • The position offers a rate of up to £600 a day, and candidates should have a minimum of 5 years of data engineering experience, including 2 years in a senior role.
  • The role involves designing and implementing data pipelines and ML infrastructure on AWS, collaborating with various teams to deliver production-grade ML systems.
  • Key skills required include deep expertise in AWS services, strong Python and SQL skills, and familiarity with containerization and MLOps best practices.
  • Bonus points are given for experience with real-time data streaming and previous work in high-compliance industries like finance or healthcare.

Contract Opportunity: Senior AWS Machine Learning Data Engineer

Location: London | Duration: 6 Months (Extension Possible) | Start Date: ASAP

Rate: Up to £600 a day (Inisde IR35)

Are you a cloud-native data engineer with a passion for building intelligent systems? I'm looking for a Senior AWS Machine Learning Data Engineer to a cutting-edge team on a contract basis, working on high-impact ML solutions that scale.

About the Role:

In this role, you’ll lead the design and implementation of data pipelines and ML infrastructure on AWS. You'll collaborate with data scientists, architects, and product teams to deliver production-grade ML systems across a variety of domains — from predictive analytics to real-time personalization.

? What You’ll Do:
  • Architect and build scalable, secure, and maintainable data pipelines on AWS (Glue, Lambda, Step Functions, S3, Redshift, etc.)

  • Operationalize machine learning models in production environments using SageMaker or custom deployment frameworks

  • Automate and optimize ETL/ELT processes for structured and unstructured data

  • Integrate CI/CD and MLOps best practices for rapid model iteration and deployment

  • Collaborate across teams to align ML engineering efforts with business needs

? What We’re Looking For:
  • 5+ years of data engineering experience, with 2+ years in a senior role

  • Deep expertise with AWS services (S3, Glue, Lambda, SageMaker, Redshift, etc.)

  • Strong Python and SQL skills; experience with PySpark a bonus

  • Familiarity with containerization (Docker), orchestration (Airflow, Step Functions), and infrastructure as code (Terraform/CDK)

  • Solid understanding of machine learning model lifecycle and best practices for deployment at scale

  • Excellent communication skills and the ability to work independently in a remote environment

? Bonus Points:
  • Experience with real-time data streaming (Kafka, Kinesis)

  • Exposure to data governance and security best practices in cloud environments

  • Previous work in a high-compliance industry (finance, healthcare, etc.)

Why Join?
  • Work with a passionate, experienced team on leading-edge projects

  • Influence architecture and best practices from day one

  • Opportunity for contract renewal

InterQuest Group is acting as an employment agency for this vacancy. InterQuest Group is an equal opportunities employer and we welcome applications from all suitably qualified persons regardless of age, disability, gender, religion/belief, race, marriage, civil partnership, pregnancy, maternity, sex or sexual orientation. Please make us aware if you require any reasonable adjustments throughout the recruitment process.

Apply now in a few quick clicks

In order to submit this application, a Reed account will be created for you. As such, in addition to applying for this job, you will be signed up to all Reed’s services as part of the process. By submitting this application, you agree to Reed’s Terms and Conditions and acknowledge that your personal data will be transferred to Reed and processed by them in accordance with their Privacy Policy.