Senior Data Engineer

Job Description

Position Summary

The engineering team plays a key role in designing and building high-impact digital solutions that transform how surgical and clinical environments operate. Through advanced data systems and real-time analytics, the company empowers healthcare teams to optimize efficiency, quality, and outcomes.

We are seeking a Senior Data Engineer who will design and implement modern data infrastructure, enable analytics and machine learning capabilities, and contribute to the continuous evolution of the our clients global data platform. The position reports to the Data Engineering Lead based in the UK.

Main Responsibilities

• Design, evolve, and maintain scalable data architectures that meet performance, reliability, and cost requirements.
• Build, automate, and monitor data pipelines for both batch and streaming workflows.
• Develop and maintain robust data models and cataloging systems.
• Optimize performance across technologies such as Spark, Presto, Athena, and Postgres.
• Implement automated testing, anomaly detection, and data validation frameworks (e.g., Great Expectations).
• Set up monitoring and incident response processes to ensure data quality and system reliability.
• Enforce strict data security standards, including encryption, anonymization, and compliance with privacy regulations such as GDPR and HIPAA.
• Manage cloud infrastructure using Infrastructure as Code (e.g., Terraform).
• Collaborate with cross-functional teams — including Data Science, Analytics, Product, and Operations — to design well-documented, reusable datasets and APIs.
• Develop data-driven products such as dashboards, analytics layers, and ML-ready pipelines.
• Mentor junior engineers, promote best practices, maintain documentation, and ensure CI/CD standards are followed.

Required Qualifications

• Bachelor’s degree in Computer Science, Mathematics, Engineering, or a related field (or equivalent experience).
• At least 5 years of experience in data engineering, with a focus on cloud-based data platforms and pipelines.
• Proven experience designing and managing data infrastructure on AWS or similar cloud environments.
• Hands-on knowledge of tools such as S3, Glue, EMR, Lambda, and Aurora (or equivalent).
• Strong programming skills in Python and SQL.
• Ability to work collaboratively in agile, cross-functional teams