AWS Data Engineer (Python | Kafka) - SC Cleared

SR2 REC LTD

Greater London

On-site

GBP 68,000 - 90,000

Full time

9 days ago

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Job summary

SR2 REC LTD in London is seeking an experienced Data Engineer to design, build and support secure, scalable data pipelines in a government data and analytics programme. You will work across cloud infrastructure, streaming technologies and production data environments, with active SC clearance required.

The role focuses on Python development, AWS services and Kafka-based streaming, plus infrastructure as code and robust data workflows.

Qualifications

  • Strong Python engineering experience.
  • Strong AWS experience.
  • Experience with Apache Kafka / streaming data.
  • Experience with Terraform.
  • Strong SQL skills.
  • ETL/ELT and data pipeline development.
  • CI/CD and automated deployment.

Responsibilities

  • Design, build and maintain data pipelines and data-processing services.
  • Develop production-quality solutions using Python and SQL.
  • Build and support Kafka-based streaming and event-driven architectures.
  • Work with AWS services and cloud-native data platforms.
  • Manage infrastructure through Terraform / Infrastructure as Code.
  • Support data profiling, mapping and transformation.
  • Re-engineer pipelines as upstream systems or requirements change.
  • Contribute to monitoring, incident investigation and production support.
  • Collaborate with engineering and delivery teams to improve data services.

Skills

Python
AWS
Kafka/Streaming
SQL
ETL/ELT
CI/CD
Production data services

Tools

Terraform

Job description

SR2 REC LTD in London is seeking an experienced Data Engineer to design, build and support secure, scalable data pipelines in a government data and analytics programme. You will work across cloud infrastructure, streaming technologies and production data environments, with active SC clearance required.

The role focuses on Python development, AWS services and Kafka-based streaming, plus infrastructure as code and robust data workflows.

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