Senior Engineer, Digital Measurement Platform & Data Infrastructure

Description

The team builds backend platforms, data pipelines, orchestration frameworks and machine learning deployment capabilities that power digital measurement and AI-driven products.

You will help take new algorithms and engineering ideas into production quickly and at large scale, testing them for viability first so the resulting systems are reliable, scalable and ready for production.

The work covers the full cycle of designing, building, testing, deploying and supporting production systems for data ingestion, feature processing, algorithm execution, model deployment and AI/ML delivery.

Responsibilities

• Design and build backend services, APIs, data pipelines and orchestration frameworks for digital measurement and AI-enabled products.
• Implement production systems for data ingestion, feature processing, algorithm execution, model deployment and automation of machine learning workflows.
• Work with software, data and machine learning engineers and architects to turn advanced algorithms into scalable production systems.
• Build and support backend platforms and automation that handle complex, high-dimensional data and machine learning workloads at scale.
• Improve the performance, scalability, reliability and efficiency of backend systems, data pipelines and ML production workflows using a range of techniques.
• Guide testing and validation of services, pipelines and deployment capabilities so they are production-ready and operationally reliable.
• Help shape engineering standards, software quality, code reviews and platform best practices.
• Mentor and lead engineers on the team while doing hands-on individual contributor work.

Requirements

• A Bachelor's or Master's degree in Computer Science, Software Engineering, Computer Engineering, Information Systems, Artificial Intelligence or a related field.
• 8+ years designing, building and supporting production backend systems, distributed applications, data pipelines and machine learning deployment environments.
• Experience building APIs, backend services, workflow orchestration systems and scalable data processing applications.
• Programming experience in Python, Java, C++ or equivalent.
• Experience deploying and supporting machine learning, data processing and analytics workloads in production.
• Experience with cloud-native architectures, Kubernetes-based environments, CI/CD pipelines and modern development practices.
• Experience with large-scale production systems, cloud environments and real-world datasets.
• Experience with software testing, monitoring, observability, performance optimization and engineering best practices.
• Experience collaborating with engineering, data science, product and architecture teams.
• The company provides clinical research services, commercial insights and healthcare intelligence to life sciences and healthcare companies, helping bring new medical treatments to market.
• Candidates must submit truthful, complete information. Any false statement, misrepresentation or material omission can lead to disqualification or later dismissal, as allowed by law.

Conditions

The potential annualized base pay range is €40,200.00 to €60,200.00.

Actual base pay depends on factors such as qualifications, knowledge, skills, education, experience, location and schedule (full or part-time).

Incentive plans, bonuses or other compensation may be offered depending on the position, alongside health, welfare and other benefits.

Benefits

• Incentive plans, bonuses and other forms of compensation may be offered, along with a range of health and welfare benefits.