Senior Manager, Artificial Intelligence Data Engineer

Regeneron

Senior Manager overseeing AI-driven digital transformation of clinical data infrastructure. Leading data strategy implementation with a cross-functional team in a fast-growing biotechnology company.

Posted 6/3/2026full-timeArmonk • New Jersey, New York • 🇺🇸 United StatesSenior💰 $150,500 - $245,500 per yearWebsite

Tech Stack

Tools & technologies

Amazon RedshiftAWSAzureBigQueryCloudGoogle Cloud PlatformPythonSQL

About the role

Key responsibilities & impact

Work with a cross-functional team to optimize and implement our data strategy with a focus on optimization for digital transformation and the use of AI/ML
Design and document end-to-end data architectures that support diverse analytic, operational, and research needs.
Facilitate the implementation of a modern data platform (e.g. Snowflake, Databricks, etc.)
Identify opportunities and implement solutions to increase data interoperability and standardization among systems and across other business units.
Develop and implement pipelines to monitor and improve both internal and external (i.e., from CRO partners) data quality.
Work with informatics and AI engineers optimizing the utility of data for their respective pipelines.
Monitor and optimize the performance of data architectures and platforms.
Develop or implement critical metrics to measure the impact of the overall data strategy.
Stay up to date with the latest advances in the field and, as appropriate, evaluate them for adoption

Requirements

What you’ll need

An advanced degree in computer science, statistics, biomedical informatics, or a related field is preferred (PhD + 2 years of experience or an MS + 4 years of relevant experience).
A minimum of 5 years’ experience developing and leading the implementation of data engineering solutions, including accountability for the success of the implementation, in life sciences or healthcare
Demonstrated expertise in designing and maintaining infrastructure and architecture for clinical or biomedical data in a healthcare or life sciences setting.
Expertise in modern data platforms (e.g., Snowflake, Redshift, BigQuery, Databricks) and programming languages such as Python, SQL, R, etc.
Maintain and manage code repositories (e.g Bitbucket) ensuring clean, well-documented code with proper version control.
Proficiency in cloud architecture (e.g. AWS, Azure, GCP) and DevOps practices. Recognized certifications are a plus.
Experience building, scaling, and maintaining pipelines for structured and unstructured data. Ability to integrate pipelines across the enterprise is essential.
Deep understanding of regulatory frameworks (HIPAA, GDPR, 21 CFR Part 11) and clinical data standards (CDISC, HL7, FHIR).
Knowledge of machine learning pipelines and integration with clinical data platforms.
May require travel up to 20%.

Benefits

Comp & perks

Health and wellness programs (including medical, dental, vision, life, and disability insurance)
Fitness centers
401(k) company match
Family support benefits
Equity awards
Annual bonuses
Paid time off
Paid leaves (e.g., military and parental leave) for eligible employees at all levels!

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Hard Skills & Tools

data engineeringdata architecturedata qualitymachine learningPythonSQLRcloud architectureDevOpsdata pipelines

Soft Skills

cross-functional collaborationproblem-solvingcommunicationleadershiporganizational skills