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# Senior Data Engineer

- **Company:** Harnham
- **Location:** London, UK
- **Experience:** Expert
- **Salary:** £60,000.0 - £80,000.0
- **Contract:** Permanent contract
- **Skills:** Artificial Intelligence, Amazon Web Services, Business Analytics Applications, Data Analysis, Microsoft Azure, Cloud Computing, Continuous Integration, Data Architecture, Information Engineering, Data Governance, Data Infrastructure, Extract Transform Load (ETL), Data Systems, Dimensional Modeling, Python (Programming Language), Machine Learning, SQL Databases, Cloud Platform System, Sql Optimization, Git Flow, Deployment Automation, Data Pipelines
- **Published:** September 11, 2026
- **Apply:** https://www.reed.co.uk/jobs/senior-data-engineer/57334140

## About the Role

The successful Senior Data Engineer will have the following skills and experience:

 * Strong commercial experience in Data Engineering and cloud-based data platforms.
 * Advanced SQL skills and experience building transformation pipelines.
 * Strong Python capability for orchestration, automation, and data tooling.
 * Excellent understanding of dimensional modelling and scalable data architecture.
 * Experience working with cloud technologies such as Azure, AWS, or GCP.
 * Knowledge of CI/CD practices, Git workflows, and deployment lifecycle management.
 * Experience implementing data governance, monitoring, and quality controls.
 * Ability to work effectively with cross-functional teams and communicate complex technical concepts clearly.
 * A collaborative approach with strong problem-solving and stakeholder engagement skills

## Description

As a Senior Data Engineer, you will be responsible for designing, building, and maintaining the data foundations that power a suite of AI-enabled products and analytics solutions.

Specifically, you can expect to be involved in the following:

 * Design and develop scalable ETL and ELT pipelines across operational, analytical, and AI data environments.
 * Build robust SQL and Python-based data solutions for production use.
 * Develop and enhance data models that support analytics, machine learning, and customer insight initiatives.
 * Contribute to CI/CD processes, deployment automation, and version-controlled engineering practices.
 * Collaborate with data scientists, product teams, and engineers to deliver reliable and scalable solutions.
 * Implement monitoring, validation, data quality controls, and governance processes.
 * Support the integration of machine learning outputs into production environments.
 * Mentor colleagues and contribute to engineering standards, documentation, and best practice development


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