Location: Hybrid, New York

Medidata follows a hybrid office policy in which employees who are hired for an in-person position are expected to work on site a certain number of days per week in accordance with Company policy.

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:

Reporting to the Senior Manager, Engineering and Architecture, the Senior Staff Engineer, Study Experience Engineering will lead the design, development, and implementation of scalable, cloud-native data engineering solutions to power analytics, data science, and operational decision-making. You will architect and build advanced data pipelines and platforms that deliver clean, reliable, and timely data across the organization.

This is a senior technical leadership role that requires not only strong hands-on engineering expertise but also the ability to lead and mentor teams, influence architectural decisions, and drive data engineering best practices across the enterprise.

Responsibilities:

• Architect and build large-scale, automated, and resilient data pipelines and platforms to support advanced analytics and machine learning initiatives.
• Contribute to and integrate with backend services built in Java to ensure seamless data flow between systems and pipelines.
• Lead technical direction for data engineering initiatives, ensuring solutions are performant, secure, cost-efficient, and aligned with business priorities.
• Develop and maintain ETL/ELT workflows using orchestration frameworks such as Apache Airflow, Snowflake Tasks, and related scheduling tools.
• Design and optimize data models and schemas in Snowflake for both real-time and batch processing.
• Work with open table formats such as Apache Iceberg to enable scalable, flexible data lakehouse architectures.
• Work with streaming data using Apache Kafka and other event-driven frameworks to enable real-time analytics.
• Collaborate closely with data scientists, software engineers, product owners, and business stakeholders to translate complex business requirements into robust technical solutions.
• Implement data quality, governance, and observability frameworks to ensure trusted data delivery.
• Lead and mentor data engineering teams, fostering a culture of technical excellence, innovation, and accountability.
• Partner with platform engineering teams to scale infrastructure on Amazon Web Services (AWS), ensuring reliability, security, and cost optimization.
• Contribute to and enforce best practices in CI/CD, code review, version control (GitHub), testing, and documentation.

Qualifications:

• 10+ years of experience in data engineering or software engineering, with a strong focus on cloud-native data platforms.
• Proven experience leading technical projects and teams in complex, enterprise-scale environments.
• Deep expertise with AWS services (e.g., S3, Glue, Lambda, EMR, Redshift, Kinesis) and Snowflake data warehouse.
• Advanced proficiency in Python, SQL, and Java for building and integrating data solutions.
• Hands-on experience with data orchestration using Airflow or similar workflow tools.
• Strong knowledge of streaming data architecture using Kafka or equivalent technologies.
• Experience working with Iceberg or similar table formats for lakehouse architectures.
• Experience implementing data governance, data lineage, and observability frameworks.
• Strong understanding of modern software development lifecycle, including CI/CD pipelines, automated testing, and infrastructure as code.
• Excellent communication skills, with the ability to present complex technical solutions to both technical and non-technical stakeholders.
• A growth mindset and the ability to influence architecture and strategy across multiple teams.

Bonus Skills:

• Experience with containerization and orchestration (e.g., Docker, Kubernetes).
• Experience with data testing and validation frameworks such as Great Expectations.
• Knowledge of data cataloging and metadata management tools (e.g., Apache Atlas, Alation).
• Experience in regulated industries (e.g., Life Sciences, Healthcare) with a focus on data security and compliance.

The salary range posted below refers only to positions that will be physically based in New York City. As with all roles, Medidata sets ranges based on a number of factors including function, level, candidate expertise and experience, and geographic location.

The salary range for positions that will be physically based in the NYC Metro Area is $157,500-$210,000.

Base pay is one part of the Total Rewards that Medidata provides to compensate and recognize employees for their work. Most sales positions are eligible for a commission on the terms of applicable plan documents, and many of Medidata's non-sales positions are eligible for annual bonuses. Medidata believes that benefits should connect you to the support you need when it matters most and provides best-in-class benefits, including medical, dental, life and disability insurance; 401(k) matching; flexible paid time off; and 10 paid holidays per year.

Applications will be accepted on an ongoing basis until the position is filled.

#LI-Hybrid