Job description

Location : This is a hybrid remote/in-office role. 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 following Company policy. About our Company : Medidata is powering smarter treatments and healthier people through digital solutions to support clinical trials. Celebrating over 25 years of ground-breaking technological innovation across more than 38,000 trials and 12 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 registered users across approximately 2,300 customers trust Medidata's seamless, end-to-end platform to improve patient experiences, accelerate clinical breakthroughs, and bring therapies to market faster. A Dassault Systèmes brand (Euronext Paris: FR0014003TT8, DSY.PA), Medidata is headquartered in New York City and has been recognized as a Leader by Everest Group and IDC. Discover more at www.medidata.com . Listen to our latest podcast, from Dreamers to Disruptors , and follow us at @Medidata. Our Team The Data Nexus team within Medidata Study Experience builds the modern data foundation that connects clinical applications, customer data, analytics, and enterprise integrations. Our mission is to make clinical operational data easier to ingest, migrate, transform, govern, and consume at scale. We build capabilities spanning large-scale customer and third-party study migrations, near-real-time CDC and streaming pipelines, reusable data products, analytics and reporting, and cross-product data integrations. We are modernizing our platform around cloud-native and lakehouse architectures using technologies including AWS, Snowflake, dbt, Airflow, Apache Flink, Amazon S3, AWS Glue, and Apache Iceberg. We treat data as a product and build trusted, reusable capabilities that power Medidata applications, customer integrations, analytics, and emerging AI/ML experiences. Who you are: As a Staff Data Engineer, you will be a hands-on technical leader responsible for solving complex data engineering problems, influencing architecture and technical direction, driving strategic initiatives across teams, and raising engineering standards across Data Nexus. What You'll Do • Lead the architecture, design, and implementation of scalable data ingestion, migration, CDC, streaming, and ETL/ELT solutions. • Provide technical leadership for large-scale customer and third-party clinical study data migrations. • Design and build reusable data products and services supporting Medidata applications, analytics, reporting, AI/ML, and customer integrations. • Drive modernization across cloud data warehousing, workflow orchestration, streaming, and lakehouse architectures. • Design scalable data models, transformation frameworks, APIs, and integration patterns for complex operational and analytical workloads. • Improve data quality, observability, performance, reliability, security, and cost efficiency across the platform. • Lead technical design and architecture discussions and collaborate across Product, Engineering, QA, Architecture, and other teams to deliver complex initiatives. • Mentor engineers, review designs and code, and establish engineering patterns and best practices across the team. • Leverage AI-assisted engineering tools such as GitHub Copilot, Claude Code, Cursor, and similar technologies to accelerate development, refactoring, testing, troubleshooting, and documentation. • Identify opportunities to apply Generative AI and intelligent data experiences to improve how users discover, understand, and interact with clinical data. Qualifications • Bachelor's or Master's degree in Computer Science, Engineering, Data Science, or a related discipline, or equivalent practical experience. • 8+ years of professional software or data engineering experience, including experience designing and operating large-scale production data systems. • Strong understanding of modern data engineering patterns including ETL/ELT, Change Data Capture, streaming, data modeling, data migration, and distributed data processing. • Strong software engineering fundamentals with proficiency in SQL and experience with languages such as Python, Java, Scala, or equivalent. • Experience with modern cloud data platforms, transformation frameworks, and workflow orchestration technologies such as Snowflake, dbt, Airflow, or comparable platforms. • Experience designing and operating cloud-native data solutions on AWS or another major cloud platform. • Hands-on experience with streaming and lakehouse technologies such as Apache Flink, Kafka, Apache Iceberg, Amazon S3, and enterprise data catalog technologies such as AWS Glue or comparable platforms. • Strong understanding of scalability, performance, security, data quality, observability, reliability, and production operations. • Demonstrated ability to lead complex technical initiatives spanning multiple applications, systems, and engineering teams. • Strong communication and technical leadership skills, including mentoring engineers and influencing architectural and engineering decisions. • Practical experience incorporating AI-assisted development tools such as GitHub Copilot, Claude Code, Cursor, or equivalent tools into software engineering workflows. Preferred Qualifications • Experience building AI-enabled data applications and Generative AI use cases such as Retrieval-Augmented Generation (RAG), natural-language-to-SQL, conversational analytics, intelligent data discovery, or semantic search. • Experience with LLMs, embeddings, vector databases, metadata enrichment, knowledge retrieval, or similar AI/data architectures. • Experience applying AI to data engineering use cases such as automated schema mapping, data transformation generation, data classification, anomaly detection, data-quality analysis, or intelligent pipeline troubleshooting. • Experience integrating AI/ML models or agentic workflows with enterprise data platforms, APIs, and production data pipelines. • Familiarity with AI platform concepts such as model gateways, MCP, prompt and context management, evaluation, observability, security, and responsible AI practices. • Experience with large-scale enterprise or clinical data migrations, analytics platforms, APIs, or reusable data products. • Experience with infrastructure automation and modern engineering practices using technologies such as Kubernetes, Terraform, GitHub Actions, or equivalent. • Experience in life sciences, healthcare, clinical trials, or another regulated environment. 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 $135,000-180,000 • The salary range for positions that will be physically based in all other locations within the United States is $120,750-161,000. 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 benefits, including medical, dental, life and disability insurance, 401(k) matching, family leave, flexible paid time off; and 10 paid holidays per year. #LI-MM1 #LI-Hybrid Equal Employment Opportunity : In order to provide equal employment and advancement opportunities to all individuals, employment decisions at Medidata are based on merit, qualifications and abilities. Medidata is committed to a policy of non-discrimination and equal opportunity for all employees and qualified applicants without regard to race, color, religion, gender, sex (including pregnancy, childbirth or medical or common conditions related to pregnancy or childbirth), sexual orientation, gender identity, gender expression, marital status, familial status, national origin, ancestry, age, disability, veteran status, military service, application for military service, genetic information, receipt of free medical care, or any other characteristic protected under applicable law. Medidata will make reasonable accommodations for qualified individuals with known disabilities, in accordance with applicable law. We will accept applications on an ongoing basis until we fill the position. Inclusion statement In order to provide equal employment and advancement opportunities to all individuals, employment decisions at 3DS are based on merit, qualifications and abilities. 3DS is committed to a policy of non-discrimination and equal opportunity for all employees and qualified applicants without regard to race, color, religion, gender, sex (including pregnancy, childbirth or medical or common conditions related to pregnancy or childbirth), sexual orientation, gender identity, gender expression, marital status, familial status, national origin, ancestry, age (40 and above), disability, veteran status, military service, application for military service, genetic information, receipt of free medical care, or any other characteristic protected under applicable law. 3DS will make reasonable accommodations for qualified individuals with known disabilities, in accordance with applicable law. Qualified applicants with arrest or conviction records will be considered for employment in accordance with applicable state laws and local ordinances. We are committed to fair employment practices and will evaluate all candidates based on their qualifications, regardless of past arrest or conviction history. Salary Pay Transparency Compensation for the role will be commensurate with experience. The total expected compensation range will be between $135000 and $180000, representing the base salary (or annualized salary based on estimated hourly compensation) and target bonus.

Requirements

Must-haves

Location : This is a hybrid remote/in-office role.
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 following Company policy.
Lead the architecture, design, and implementation of scalable data ingestion, migration, CDC, streaming, and ETL/ELT solutions.
Provide technical leadership for large-scale customer and third-party clinical study data migrations.
Design and build reusable data products and services supporting Medidata applications, analytics, reporting, AI/ML, and customer integrations.
Drive modernization across cloud data warehousing, workflow orchestration, streaming, and lakehouse architectures.
Design scalable data models, transformation frameworks, APIs, and integration patterns for complex operational and analytical workloads.
Improve data quality, observability, performance, reliability, security, and cost efficiency across the platform.
Lead technical design and architecture discussions and collaborate across Product, Engineering, QA, Architecture, and other teams to deliver complex initiatives.
Mentor engineers, review designs and code, and establish engineering patterns and best practices across the team.
Leverage AI-assisted engineering tools such as GitHub Copilot, Claude Code, Cursor, and similar technologies to accelerate development, refactoring, testing, troubleshooting, and documentation.
Identify opportunities to apply Generative AI and intelligent data experiences to improve how users discover, understand, and interact with clinical data.
Bachelor's or Master's degree in Computer Science, Engineering, Data Science, or a related discipline, or equivalent practical experience.
8+ years of professional software or data engineering experience, including experience designing and operating large-scale production data systems.
Strong understanding of modern data engineering patterns including ETL/ELT, Change Data Capture, streaming, data modeling, data migration, and distributed data processing.
Strong software engineering fundamentals with proficiency in SQL and experience with languages such as Python, Java, Scala, or equivalent.
Experience with modern cloud data platforms, transformation frameworks, and workflow orchestration technologies such as Snowflake, dbt, Airflow, or comparable platforms.

Nice-to-haves

Experience with LLMs, embeddings, vector databases, metadata enrichment, knowledge retrieval, or similar AI/data architectures.
Experience integrating AI/ML models or agentic workflows with enterprise data platforms, APIs, and production data pipelines.
Familiarity with AI platform concepts such as model gateways, MCP, prompt and context management, evaluation, observability, security, and responsible AI practices.
Experience with large-scale enterprise or clinical data migrations, analytics platforms, APIs, or reusable data products.
Experience with infrastructure automation and modern engineering practices using technologies such as Kubernetes, Terraform, GitHub Actions, or equivalent.
Experience in life sciences, healthcare, clinical trials, or another regulated environment.
As with all roles, Medidata sets ranges based on a number of factors including function, level, candidate expertise and experience, and geographic location.

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Benefits

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Dental

401(K)

Pto

Paid Time Off