Staff Applications Engineer
About our Company:
Medidata is powering smarter treatments and healthier people through digital solutions to support clinical trials. Celebrating 25 years of ground-breaking technological innovation across more than 36,000 trials and 11 million patients, Medidata offers industry-leading expertise, analytics-powered insights, and one of the largest clinical trial data sets in the industry. More than 1 million users trust Medidata's seamless, end-to-end platform to improve patient experiences, accelerate clinical breakthroughs, and bring therapies to market faster. Discover more at www.medidata.com.
About the Team:
As a Staff Applications Engineer in Medidata’s Platform organization, you’ll drive the technical roadmap across areas that positively impact both internal and external teams. While strengthening our data‑pipeline capabilities in support of the Medidata Platform Data Product strategy is a top priority, the team also owns a wide range of platform services and applications.
To succeed on this team, engineers need to be comfortable working across a broad technical surface area. That means your efforts will have an impact across multiple areas, such as with C# services, OLTP databases, modernizing foundational .NET Framework services, and building UI components. We value engineers who enjoy variety, can adapt to different problem spaces, and are energized by learning new technologies as part of a highly collaborative team.
Performance of these systems is also critical, as we consider the reliability, scalability, and operational excellence of these platform systems, while leveraging AIOps to shift our SRE mindset from reactive problem-solving to proactive, predictive reliability management.
Responsibilities:
● Develop new features and enhance scalability by writing straightforward, maintainable code that prioritizes architectural simplicity.
● Champion AI-first engineering practices, creatively utilizing new tools and industry advancements to solve complex data processing and reliability challenges
● Collaborate with engineering managers and architects on technical decision-making for complex systems.
● Troubleshoot production and escalated issues, providing workarounds and solutions in a timely manner.
● Mentor and guide other engineers in code reviews, and system design, ensuring best practices are followed
● Guide teams on observability, and alerting best practices, while driving the adoption of machine learning and agentic approaches to anomaly detection and intelligent alerting
● Lead hazards reviews and post-incident analyses, driving proactive and preventive reliability improvements leveraging AI to synthesize insights and develop self-healing systems.
● Promote a culture of collaboration and communication within the team.
● Sync with product, PMO, and QA teams to deliver high-quality software.
● Participate in cross-functional projects, contributing to broader engineering initiatives.
● Stay current with new technologies and apply them to improve our software offerings.
Qualifications:
● B.S. or M.S. Computer Science, Engineering, related field or relevant experience
● Proven technical leader within an Agile development environment with strong communication and collaboration skills
● 5+ years experience with full-stack large scale projects in an enterprise environment
● Proficient in .NET, Java, Python, or other object-oriented languages
● Experience designing and developing application CI/CD pipelines using tools like GitHub Actions, CloudFormation, and Terraform.
● Understanding of cloud platforms (AWS preferred) and container orchestration technologies (Kubernetes required)
● Strong understanding of observability concepts (metrics, logs, traces, alerting) and hands-on experience with modern monitoring, telemetry tools, and automation
● Experience in AIOps creating and implementing machine learning and agentic monitoring and action tools, a plus
● Experience with Grafana or similar cloud-native monitoring stacks, a plus
● Experience building scalable data pipelines using Kakfa, Iceberg, or similar technologies, a plus
● Experience working in a regulated environment or with clinical research processes a plus
Déclaration de diversité
Générer des preuves et des informations pour aider les sociétés pharmaceutiques, biotechnologiques, de dispositifs médicaux et de diagnostics, ainsi que les chercheurs universitaires, à générer de la valeur plus rapidement, à réduire les risques et à optimiser les résultats.
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