Senior Data Engineer — Production ML & Data Platform

Xcede Recruitment Solutions; Camden Town; Hybrid; GBP 108,000 - 132,000; Full time

Benefits offered by this job

Private medical insurance

Office gym membership

Equity/ownership shares

Dog-friendly office

Snacks and fruit in the office

Job summary

Xcede Recruitment Solutions is seeking a Senior Data Engineer to own the data infrastructure powering analytics, forecasting and production ML. The role is based in Camden, London, with an office-first approach and 4 days per week on-site.

The position is permanent and full-time (40 hours). You will design and maintain data pipelines, work with Data Science and Product teams, and deploy ML systems in production on an AWS-native stack.

Qualifications

• Strong data engineering fundamentals including pipeline design, orchestration and testing.
• Production-grade Python and SQL skills are essential.
• Experience running ML systems in production and model serving.
• Cloud experience, preferably AWS, and basic DevOps practices.
• Ownership-driven mindset and ability to operate in fast-moving environments.

Responsibilities

• Design, build and maintain data pipelines and workflows.
• Deploy and support production ML systems with monitoring and CI/CD.
• Maintain and improve an AWS-native data platform (S3, Redshift, RDS, Athena, SageMaker, Lambda).
• Write and optimize complex SQL for analytics and BI.
• Build integrations with internal services and partner systems.
• Diagnose production data issues and improve resilience.
• Collaborate with stakeholders to translate business needs into scalable data solutions.

Skills

Data engineering fundamentals

Python

SQL

Production ML systems

AWS

DevOps principles

Tools

S3

Redshift

RDS

Athena

SageMaker

Lambda

Job description

Xcede Recruitment Solutions is seeking a Senior Data Engineer to own the data infrastructure powering analytics, forecasting and production ML. The role is based in Camden, London, with an office-first approach and 4 days per week on-site.

The position is permanent and full-time (40 hours). You will design and maintain data pipelines, work with Data Science and Product teams, and deploy ML systems in production on an AWS-native stack.