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Sanderson Recruitment

Data Engineer

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Summary

A data engineer role placed via a recruitment firm, working within a client's team to build cloud-based ETL/ELT pipelines, data warehouse and lake architectures, and data models using Python, SQL/NoSQL, containerisation and Infrastructure as Code, with a focus on production ML readiness and monitoring. UK security clearance eligibility may be required.

Overview

In this role you will help grow the client’s data capability by delivering robust data engineering solutions on cloud platforms. You will work within a client context to design and implement data pipelines, architectures, and models that enable scalable data analytics. You will contribute to modern data platforms while following software development practices and pursuing production ML readiness and monitoring. This opportunity offers exposure to cross-functional collaboration and the chance to shape the client’s data-driven transformation.

Responsibilities
  • Develop ETL/ELT pipelines and maintain data warehousing and lake architectures
  • Leverage Python to build and maintain data tooling and pipelines
  • Work with SQL and NoSQL databases and distributed computing frameworks
  • Apply software development best practices and containerisation
  • Utilise Infrastructure as Code tools to manage cloud resources
  • Contribute to data modelling and system architecture decisions
  • Understand and support monitoring of ML models in production
  • Engage with the client and secure UK security clearance when required
  • Collaborate with cross-functional teams to deliver data solutions
Key requirements
  • Strong proficiency in Python
  • Extensive experience with cloud platforms
  • Experience with data warehousing and lake architectures
  • ETL/ELT pipeline development
  • SQL and NoSQL databases
  • Distributed computing frameworks
  • Software development best practices
  • Containerisation tools
  • Experience with Infrastructure as Code tools
  • Strong understanding of data modelling and system architecture
  • Knowledge of common machine learning frameworks and models
  • Understanding of approaches to monitoring ML models in production
  • Willingness and eligibility to undergo UK security clearance
  • Python
  • Cloud platforms
  • Data warehousing
  • Data lake architectures
  • ETL/ELT
  • SQL

Skills

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See also

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