Senior Data Engineer - AI-Enabled Data Platform & Cloud

Harnham; Greater London; On-site; GBP 90,000 - 130,000; Full time

Benefits offered by this job

Competitive salary

Collaborative culture

Clear progression opportunities

Job summary

Harnham is seeking a Senior Data Engineer to design and deliver data foundations powering analytics and AI solutions. You will work on modern cloud technologies and enterprise-scale data challenges, shaping scalable ETL/ELT pipelines and robust data models.

You will collaborate with Product, Engineering and Data Science teams, mentoring peers and implementing best practices to ensure reliable, scalable data platforms across Azure, AWS and GCP environments.

Qualifications

• Experience designing scalable ETL/ELT pipelines.
• Strong modelling for analytics and AI workloads.
• Cloud-native data solutions and data platforms.
• Exposure to CI/CD pipelines and DevOps practices.
• Knowledge of DataOps and engineering best practices.
• Excellent problem-solving and stakeholder engagement.

Responsibilities

• Design and develop scalable ETL/ELT pipelines.
• Build and optimise data models supporting analytics and AI workloads.
• Develop and maintain cloud-native data solutions.
• Support CI/CD implementation and deployment processes.
• Integrate AI outputs into production environments.
• Implement monitoring, governance, and operational best practices.
• Collaborate with Product, Engineering, and Data Science teams.
• Mentor colleagues and contribute to engineering standards.

Skills

SQL

Python

Dimensional modelling

Data warehousing

CI/CD / DevOps

DataOps

Stakeholder engagement

Problem solving

Tools

Azure

AWS

GCP

Job description

Harnham is seeking a Senior Data Engineer to design and deliver data foundations powering analytics and AI solutions. You will work on modern cloud technologies and enterprise-scale data challenges, shaping scalable ETL/ELT pipelines and robust data models.

You will collaborate with Product, Engineering and Data Science teams, mentoring peers and implementing best practices to ensure reliable, scalable data platforms across Azure, AWS and GCP environments.