Data Engineer | Python | SQL | Data Pipelines | Data Infrastructure | Snowflake | AWS | London, Hybrid

Position Overview

We are seeking an experienced Data Engineer to help build and maintain the data infrastructure powering a large-scale AI-driven clinical monitoring platform. You will design and operate robust data pipelines that ingest, transform, and distribute sensitive healthcare data originating from Electronic Health Record (EHR) systems, medical devices, and hospital information systems.

Working closely with backend engineers, ML engineers, clinical teams, and customer integration partners, you will ensure the reliable, secure, and compliant flow of patient data across operational and analytical systems.

Your work will directly support predictive analytics and machine learning models that identify early signs of clinical deterioration, helping clinicians intervene sooner and improve patient outcomes. This is a hands-on role where production-grade data engineering, reliability, and healthcare compliance are critical.

Key Responsibilities

Data Pipeline & Integration Development

Design, build, and maintain scalable data pipelines to ingest healthcare data from customer EHR systems and hospital databases.
Develop integrations using:
REST APIs and webhook-driven workflows
Database log shipping and change data capture (CDC) mechanisms, including Microsoft SQL Server–based systems
Transform, validate, and normalise incoming clinical data before loading it into operational and analytical data platforms.
Ensure pipelines are robust, fault-tolerant, and capable of handling large-scale data volumes.

Healthcare Data & EHR Integrations

Integrate and manage healthcare data domains including:
Admissions, Discharges, and Transfers (ADT)
Conditions, medications, and allergies
Clinical notes and progress notes
Vital signs and physiological measurements
Work with healthcare interoperability standards and protocols such as:
HL7 v2
FHIR
Partner with customer technical teams to support onboarding, troubleshooting, and ongoing data reliability.

Data Platforms & Warehousing

Take ownership of operational databases and analytical data warehouses.
Design schemas and transformations that support both real-time application requirements and downstream analytics and ML workloads.
Optimise performance, cost, and scalability across cloud-based data platforms.

Cloud Deployment & Operations

Deploy and operate data pipelines and services in AWS.
Implement monitoring, logging, alerting, and operational dashboards for data workflows.
Support production reliability, incident response, and continuous improvement initiatives.

Security, Compliance & Data Quality

Ensure all data pipelines meet healthcare security and privacy requirements.
Apply best practices for handling sensitive healthcare data, including access control, encryption, and audit logging.
Maintain clear documentation of data flows, transformations, and operational processes.

Collaboration & Enablement

Work closely with Data Science and ML teams to support:
Model training and evaluation
Feature generation and data labelling workflows
Collaborate with backend engineering teams to develop tooling for data ingestion, validation, and monitoring.
Participate in architecture discussions to ensure scalability and reliability as the platform grows.

Required Qualifications

5+ years of experience in Data Engineering, Backend Engineering, or a related role.
Strong proficiency in Python for data pipeline and backend development.
Strong proficiency in SQL.
Hands-on experience with relational databases and cloud data warehouses, including schema design and performance optimisation.
Experience integrating data from Microsoft SQL Server, including log shipping or CDC-style approaches.
Experience building high-throughput data pipelines from ingestion through transformation and storage.
Experience deploying and operating production systems within a major cloud provider environment (AWS preferred).
Familiarity with APIs, webhooks, and event-driven architectures.
Experience working with sensitive or regulated data.

Preferred Qualifications

Experience integrating with EHR systems.
Familiarity with healthcare interoperability standards such as HL7 and FHIR.
Experience supporting machine learning or data science teams.
Experience with data orchestration, workflow management, or streaming systems.
Background in healthcare, medical devices, or clinical data systems.
Exposure to healthcare compliance and security best practices.

What You Bring

Strong ownership mindset across the full data lifecycle, from ingestion through analytics.
A focus on data quality, reliability, and operational excellence.
Comfort operating within complex customer integration environments.
Strong communication skills across engineering, data, and clinical stakeholders.
Motivation to work on technology that directly improves patient care.

Why Join Us

You will have the opportunity to:

Work on real-world healthcare challenges with measurable patient impact.
Build data systems that support clinical-grade AI and ML applications.
Take ownership within a fast-growing, mission-driven environment.
Collaborate with a highly skilled, multidisciplinary team.

Apply Now

Data Engineer | Python | SQL | Data Pipelines | Data Infrastructure | Snowflake | AWS | London, Hybrid

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