Gilead Sciences · 5 days ago
Sr Manager, IT Data Engineering
Gilead Sciences is a biopharmaceutical company focused on developing therapies that improve lives and address major health challenges. The Delivery Lead will serve as the primary technical leader for data, analytics, and AI initiatives supporting enterprise operations, designing scalable data solutions and pipelines while guiding architecture, governance, quality, and compliance. The role also partners with stakeholders to deliver production-grade solutions and improve data workflows through AI-powered automation.
PharmaceuticalBiotechnologyHealthcareManufacturingBiopharmaHealth Care
Comp. & BenefitsH1B Sponsor Likely
Responsibilities
Design and implement scalable, secure, and high-performance data solutions across a cloud environment, including AWS and Databricks
Define and enforce data engineering standards, best practices, and architectural patterns
Collaborate with a highly motivated team to evaluate and integrate emerging technologies that enhance the capabilities of the data platform
Design, develop, and maintain ELT pipelines using AWS services, Apache Airflow, and Databricks
Drive platform evolution by identifying opportunities for AI-powered automation and implementing solutions that improve data workflows and operational efficiency
Manage the development and maintenance of data models and schema designs to support efficient data storage, processing, and retrieval
Lead schema evolution and data integration processes across source systems and target platforms
Serve as a subject matter expert for internal stakeholders and business partners by addressing technical inquiries and providing strategic guidance
Implement and maintain robust data governance, security, and compliance frameworks
Ensure data quality, security, and integrity through effective validation, cleansing, testing, monitoring, and issue-resolution processes
Establish data quality metrics, service-level agreements (SLAs), and monitoring mechanisms to ensure the reliability and trustworthiness of enterprise data assets
Ensure compliance with organizational policies and regulatory requirements related to data privacy, security, and retention
Qualification
Required
Bachelor's or master's degree in computer science, Data Engineering, Data Science, or a related field, or equivalent practical experience
3–6+ years of experience in Data Engineering, with a proven track record of designing and deploying data pipeline solutions at scale
At least 2+ years of experience building complex data science, AI/ML, or large-scale analytics solutions
Proficiency in Python and SQL; familiarity with TypeScript/JavaScript or a systems programming language such as Go or Rust
Experience with Test-Driven Development (TDD), CI/CD pipelines, and modern software engineering best practices
Experience with CI/CD platforms (e.g., GitHub Actions), containerization technologies (Docker), infrastructure-as-code principles, and cloud-native architecture patterns
Hands-on experience building and operating data and AI platforms on AWS, including services such as S3, Glue, Lambda, IAM, Bedrock, and Databricks Unity Catalog
Proficiency with Databricks (Spark), data orchestration platforms (Airflow), Tableau, Genie Spaces, and related business intelligence and analytics technologies
Hands-on experience with AI coding tools (Claude Code, GitHub Copilot, Cursor, or equivalent) and Cortex AI or comparable LLM-serving platforms
Strong understanding of how large language models generate and reason about code, with practical experience in prompt engineering as an engineering discipline
Strong understanding of data privacy, security, and regulatory requirements in healthcare environments
Experience with secrets management, audit controls, and compliance frameworks, including HIPAA, SOC 2, and 21 CFR Part 11
Ability to design and operate systems that scale across both traditional ML infrastructure and emerging agentic AI architectures
Preferred
Experience designing secure, scalable, and production-grade cloud architectures is preferred
Experience supporting analytics and AI initiatives within Cell and Gene Therapy (CGT), oncology, rare disease, or specialty pharmaceutical organizations
Experience designing multi-agent workflows, orchestration patterns, and autonomous systems for enterprise applications. Familiarity with MCP (Model Context Protocol), agent interoperability frameworks, and AI governance best practices
Experience supporting high-throughput inference workloads, large-scale batch scoring, low-latency APIs, and horizontally scalable AI/agent platforms
Experience integrating enterprise platforms and related APIs to enable end-to-end business process automation and analytics workflows
Benefits
Discretionary annual bonus
Discretionary stock-based long-term incentives (eligibility may vary based on role)
Paid time off
Company-sponsored medical, dental, vision, and life insurance plans
Hybrid eligible
Company
Gilead Sciences
Biopharmaceutical company developing HIV, cancer, and inflammation medicines.
H1B Sponsorship
Gilead Sciences has a track record of offering H1B sponsorships. Please note that this does not
guarantee sponsorship for this specific role. Below presents additional info for your
reference. (Data Powered by US Department of Labor)
Distribution of Different Job Fields Receiving Sponsorship
69%
Represents job field similar to this job
Engineering and Development
Management and Executive
Legal and Compliance
Customer Service and Support
Accounting and Finance
Marketing
Sales
Human Resources
Product Management
Public Sector and Government
Arts and Entertainment
Trends of Total Sponsorships
*2026 (85)
2025 (267)
2024 (241)
2023 (222)
2022 (208)
2021 (235)
2020 (187)
Funding
Current Stage
Public CompanyTotal Funding
$7.41BKey Investors
Abingworth
2026-05-14Post Ipo Debt· $3B
2024-11-13Post Ipo Debt· $3.5M
2024-02-29Post Ipo Equity· $210M
Leadership Team
Daniel O'Day
Chairman and Chief Executive Officer
Patrick Loerch
Senior Vice President, Clinical Data Science
Recent News
Pharmaceutical Technology
2026-09-12
2026-09-11
2026-09-10
Company data provided by crunchbase