Senior Manager, Artificial Intelligence Data Engineer

Regeneron

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Quick summary

Work type: On-site
Location: Tarrytown, NYArmonk, NYWarren, NJ
Employment: Full-time
Posted: 91 days ago
Freshness: Confirmed live today
Nearby: 99+ roles within 25 mi

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Similar $201k

$140k $253k

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This listing doesn't post a salary. Most similar roles pay $160,000–$241,750.

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About Regeneron

Regeneron is a leading science-driven biotechnology company that invents, develops, and commercializes life-transforming medicines for serious diseases.

Regeneron currently has 73 open roles on FindRole.

Listed pay typically runs $134,400–$241,200 across 46 roles with salary data.

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At a glance

TL;DR · Senior Manager, Artificial Intelligence Data Engineer

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The Senior Manager, Artificial Intelligence Data Engineer joins the Global Development team to lead a digital transformation project incorporating AI, machine learning, and automation. This role serves as a technical and strategic liaison between transformation projects and IT, focusing on modernizing clinical data infrastructure. Key responsibilities include designing end-to-end data architectures, developing schemas and data models for clinical data, and optimizing pipelines for structured and unstructured data. The engineer will manage data governance, ensure standard compliance, and automate routine workflows. Required technical skills include proficiency in Python, SQL, R, and modern data platforms like Snowflake, Databricks, Redshift, or BigQuery. Candidates must demonstrate expertise in cloud architecture, DevOps, and regulatory frameworks such as HIPAA, GDPR, and 21 CFR Part 11 within a life sciences context.

Skills

Python SQL R Snowflake Databricks AWS Azure GCP Redshift BigQuery Machine Learning DevOps Bitbucket Data Pipelines HL7 FHIR CDISC HIPAA GDPR 21 CFR Part 11

What you'll do

Develop and optimize schema and data models for clinical data to ensure standard compliance and interoperability.
Design and document end-to-end data architectures that support analytic, operational, and research needs.
Facilitate the implementation and performance optimization of modern data platforms like Snowflake or Databricks.
Develop pipelines to monitor and improve the quality of internal and external data sources.
Automate routine workflows and develop processes to improve data governance and monitoring.
Provide technical leadership and mentorship while evaluating new data engineering innovations for implementation.
Develop critical metrics to measure the impact and success of the overall data strategy.

What we're looking for

An advanced degree in computer science, statistics, biomedical informatics, or a related field is preferred (PhD + 2 years or MS + 4 years).
Minimum of 5 years of experience developing and leading data engineering solutions in life sciences or healthcare.
Demonstrated expertise in designing and maintaining infrastructure and architecture for clinical or biomedical data.
Expertise in modern data platforms like Snowflake, Redshift, BigQuery, or Databricks and programming languages such as Python, SQL, and R.
Proficiency in cloud architecture (AWS, Azure, GCP) and DevOps practices.
Recognized certifications in cloud architecture or DevOps are a plus.
Experience building and scaling pipelines for structured and unstructured data across an enterprise.
Deep understanding of regulatory frameworks (HIPAA, GDPR, 21 CFR Part 11) and clinical data standards (CDISC, HL7, FHIR).

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