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Job Title: Sr Data Engineer (Data Science)
Location: Onsite United Kingdom (Hybrid)
Employment Type: Full-Time
Experience: 5–8+ Years
About Cloudaeon
Cloudaeon is a leading Data & AI engineering company specializing in Cloud, Data Engineering, Analytics, and AI solutions. We partner with global enterprises to build modern data platforms and deliver scalable, data-driven solutions.
We are looking for an experienced Data Engineer to join a Data Science team supporting a leading UK retail enterprise client. This is a hybrid role, requiring the successful candidate to work from the client’s UK office while collaborating with globally distributed teams.
Role Overview
This is a Data Engineering role focused on building and maintaining robust, scalable data pipelines that enable advanced analytics and Data Science initiatives. This is not an AI/ML model development role. Instead, you will work closely with Data Scientists to ensure reliable, high-quality data is available for analytics and machine learning workflows.
The ideal candidate should be able to integrate into an existing delivery team with minimal ramp-up, take ownership of deliverables, and contribute independently from day one.
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Key Responsibilities
- Design, develop, and maintain scalable data pipelines to support Data Science and analytics initiatives.
- Build and manage complex workflow orchestration using Apache Airflow.
- Develop and optimize ETL/ELT pipelines using Databricks.
- Work closely with Data Scientists to support data preparation and analytical workflows.
- Manage source code using GitHub and follow collaborative development best practices.
- Work within CI/CD-driven environments to support automated deployments and continuous integration.
- Monitor, troubleshoot, and optimize data pipelines for performance, scalability, and reliability.
- Identify root causes of data issues and implement sustainable, long-term solutions.
- Contribute to improving data engineering standards, processes, and best practices.
Required Skills & Experience
- 5–8+ years of hands-on experience in Data Engineering.
- Strong expertise in Apache Airflow, including designing and managing complex workflow orchestration.
- Proven hands-on experience with Databricks for building and optimizing data pipelines.
- Strong proficiency in Python and SQL.
- Experience designing, developing, and maintaining complex, scalable ETL/ELT data pipelines.
- Experience using GitHub for version control and collaborative software development.
- Experience working in CI/CD-driven development environments.
- Proven experience supporting Data Science teams by enabling analytics and machine learning workflows.
- Ability to take ownership of end-to-end data engineering deliverables and work independently with minimal supervision.
- Strong analytical, troubleshooting, and root cause problem-solving skills.
- Excellent communication, collaboration, and stakeholder management skills.
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Nice to Have
- Exposure to MLOps concepts and tools.
- Experience working with Azure cloud services.
- Understanding of modern data platform architecture and engineering best practices.
Work Location
- Hybrid role based in the United Kingdom.
- Candidates must currently be based in the UK and have the legal right to work in the UK.
- Ability to attend the client office as required under the hybrid working model.
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