Senior Manager, Artificial Intelligence Data Engineer

Regeneron

Confirmed live 2 days ago High trust

Quick summary

Work type
On-site
Location
Tarrytown, NYArmonk, NYWarren, NJ
Salary
$150,500–$245,500 / yr
Posted
46 days ago
Freshness
Confirmed live 2 days ago

Market check

Salary context

Competitive pay

How this pay compares to similar roles

Similar $204k
This role $198k
$139k most similar roles pay here $258k

This role pays less than 53% of similar roles. Most pay $162,000–$246,150 — the shaded band above. At the midpoint, this role pays about $198k versus about $204k for comparable roles.

Based on 240 similar postings.

Employer

About Regeneron

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

Regeneron currently has 18 open roles on FindRole.

Listed pay typically runs $141,100–$243,350 across 18 roles with salary data.

Most-posted roles

View all roles at Regeneron

At a glance

TL;DR · Senior Manager, Artificial Intelligence Data Engineer

As a Senior Manager, Artificial Intelligence Data Engineer, you will join the Global Development team to drive a digital transformation initiative focused on AI, machine learning, and automation. You will serve as a technical and strategic liaison between transformation projects and IT, where you will design end-to-end data architectures, develop and optimize schema and data models for clinical data, and build automated workflows. Your daily work involves managing data pipelines, ensuring interoperability across platforms, and monitoring data quality from internal and external sources. You will utilize tools such as Snowflake, Databricks, Redshift, or BigQuery, alongside programming languages like Python, SQL, and R. The role requires expertise in cloud architecture (AWS, Azure, GCP), DevOps practices, and version control via Bitbucket while navigating clinical data standards like CDISC, HL7, and FHIR within a life sciences context.

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.
  • Implement and manage modern data platforms such as Snowflake or Databricks.
  • Build pipelines to monitor and improve the quality of internal and external data sources.
  • Automate routine workflows and develop processes to increase operational efficiency.
  • Serve as a technical liaison between transformation projects and IT departments.
  • Provide technical leadership and mentorship while evaluating new technologies for potential implementation.

What we're looking for

  • An advanced degree in computer science, statistics, biomedical informatics, or a related field is preferred.
  • A PhD with 2 years of experience or an MS with 4 years of relevant experience is preferred.
  • At least 5 years of experience developing and leading the implementation of data engineering solutions in life sciences or healthcare is required.
  • Demonstrated expertise in designing and maintaining infrastructure and architecture for clinical or biomedical data is required.
  • Expertise in modern data platforms like Snowflake, Redshift, BigQuery, or Databricks is required.
  • Proficiency in programming languages such as Python, SQL, and R is required.
  • Proficiency in cloud architecture (AWS, Azure, GCP) and DevOps practices is required.
  • Deep understanding of regulatory frameworks including HIPAA, GDPR, 21 CFR Part 11, and clinical data standards like CDISC, HL7, and FHIR is required.

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