below marketmost similar roles pay hereabove market
This role pays more than
60%
of similar roles. Most pay
$139,914–$214,900
— the blue band above.
At the midpoint, this role pays about
$194k
versus about
$177k
for comparable roles.
Based on 240 similar postings.
Employer
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
on FindRole.
Listed pay typically runs
$99,300–$198,700
across 123 roles with salary data.
The Sr Manager, Data Engineering joins the Abbott Cancer Diagnostics division to lead the data engineering organization for an assigned business domain. In this leadership role, you will own the strategy, integrated roadmap, and operating performance while managing a team of Staff Engineers and contractors. You will build governed, reusable data products and integrations that support operational applications, analytics, semantic layers, machine learning, and AI. Key responsibilities include managing technical debt tradeoffs, ensuring data quality, security, and privacy, and aligning with enterprise platform capabilities. The role requires expertise in data architecture, integration patterns, and data models within a regulated environment. Preferred technical skills include Databricks, Kafka, and cloud data services across AWS, Azure, or Google Cloud Platform to solve complex problems in life sciences and clinical-laboratory environments.
Lead, develop, and retain a domain data engineering organization including staff engineers and contractors.
Own the data engineering strategy, integrated roadmap, delivery commitments, and operating performance.
Partner with business and technology leaders to deliver governed, reusable data products and integrations.
Resolve material technical decisions and manage tradeoffs between priority, delivery, and technical debt.
Ensure data products meet standards for quality, reliability, security, privacy, and governance.
Communicate roadmap status, dependencies, risks, and decisions to senior business and technology leaders.
Represent the domain in platform, architecture, and technology-governance decisions.
What we're looking for
Bachelor’s degree in Computer Science, Information Systems, Business, or a related field, or a high school diploma plus four years of relevant experience.
Eight or more years of progressively responsible experience in data engineering, data platforms, technology delivery, or related leadership roles.
Five or more years of direct people-leadership experience, including management of engineering staff.
Demonstrated experience owning delivery, stakeholder outcomes, and operating performance for a data domain, platform, or program from planning through production support.
Demonstrated technical depth to direct data engineering work and make tradeoffs involving data architecture, integration patterns, data models, and platform decisions.
Demonstrated ability to lead delivery across direct reports, contractors, and matrixed teams, including change, risk, and dependency management.
Experience operating in a regulated or highly controlled data environment and delivering stakeholder outcomes on schedule.
Python
R
SQL
TensorFlow
PyTorch
scikit-learn
AWS
Azure
GCP
Tableau
Power BI
DataOps
CI/CD
Generative AI
Machine Learning
Big Data
Agile
Scrum
Data Governance
Data Visualization
AWS
S3
Lambda
DynamoDB
Python
SQL
dbt
Qlik Replicate
InfoSphere DataStage
CP4D
Data Vault
Git
DevOps
Agile
SCRUM
Kanban
API Development
Data Warehousing
Data Modeling