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About Abbott
Abbott Laboratories is a global healthcare company that manufactures and markets a broad and diversified line of health care products including diagnostics, medical devices, nutritionals, and branded generic pharmaceuticals. Industry: Healthcare & Medical Devices
Abbott currently has
193 open roles
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Listed pay typically runs
$99,300–$198,700
across 123 roles with salary data.
The Director, Data Engineering serves as the senior data executive for the Cancer Diagnostics division. In this leadership role, you will establish the enterprise data strategy, governance model, and analytics roadmap to shape how the division generates insights, deploys AI, and manages compliance. You will oversee the integration and staging of data while developing and maintaining data lakes, data warehouses, and data marts. Key responsibilities include defining investment priorities, identifying new data sources for business innovation, and leading regulatory compliance programs for data assets. The role requires expertise in modern cloud platforms like AWS, Azure, or GCP, distributed data systems, and contemporary data engineering frameworks. You must also possess strong knowledge of AI/ML data pipelines, metadata management, and MLOps best practices within a regulated healthcare environment.
Establish and own the enterprise data strategy, vision, and investment priorities for the Cancer Diagnostics division.
Define and implement data governance models for algorithms, analytical applications, and automated decision-making.
Lead regulatory and compliance programs for all data and analytics assets to ensure audit readiness.
Oversee the integration, staging, and maintenance of data lakes, data warehouses, and data marts.
Develop and maintain controls on data quality, interoperability, and sources to manage corporate risk.
Identify new data sources and define processes for integrating them to enable business innovation.
Manage enterprise information management principles, policies, and programs for data stewardship and advocacy.
Execute data analytics strategy practices and implement the necessary capabilities and competencies to meet business goals.
What we're looking for
Bachelor’s Degree in a related field; or Associate’s Degree and 2 years of relevant experience; or High School Diploma/GED and 4 years of relevant experience.
18 years of progressive experience in data and software engineering, digital platforms, or enterprise technology leadership.
10 years of progressive leadership experience leading cross-functional and enterprise teams.
Proven track record delivering large-scale digital and data transformation initiatives in complex, regulated, or global environments.
Expertise in modern cloud platforms (AWS, Azure, or GCP), distributed data systems, and contemporary data engineering frameworks (preferred).
Strong knowledge of AI/ML data pipelines, metadata management, and MLOps best practices (preferred).
Exceptional leadership, communication, and collaboration skills, with experience influencing senior executives and boards (preferred).
Experience managing multi-functional engineering teams and vendor/partner ecosystems (preferred).
Data Engineering
Database Management
MLOps
Generative AI
AWS
Azure
GCP
NoSQL
Data Governance
Data Security
Data Pipelines
Enterprise Analytics
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