Manager, Data Integrity (Onsite)

Alcon•Fort Worth, TX

15h•Onsite

About The Position

Alcon is seeking a hands-on data engineering leader to lead the evolution of enterprise data platforms and solutions that support commercial decision-making across North America. Based onsite in Fort Worth, Texas, the Manager, Data Integrity partners with commercial and technology organizations to build trusted, scalable data assets that influence business strategy and deliver measurable impact through analytics, automation, and AI-enabled insights. The role leads the design, development, and optimization of enterprise commercial datasets and scalable data pipelines. It establishes engineering standards, improves pipeline reliability and data quality, supports governance and stewardship, and provides technical leadership and mentorship across data engineering, modeling, and data management initiatives.

Requirements

Bachelor’s degree or equivalent years of directly related experience; alternatively, high school plus 13 years, an associate degree plus 9 years, an M.S. plus 2 years, or a Ph.D. plus 0 years.
Ability to fluently read, write, understand, and communicate in English.
Five years of relevant experience.

Nice To Haves

Experience in data engineering, analytics engineering, data architecture, data integration, data management, or related technical disciplines.
Strong SQL and Python skills, or comparable programming-language skills.
Experience building enterprise-scale datasets, data pipelines, ETL/ELT solutions, and cloud-based data platforms such as AWS or similar.
Demonstrated ownership of business-critical data assets, including data quality, governance, and reporting solutions.
Experience supporting analytics, business intelligence, Sales Operations, Marketing, or other commercial organizations.
Ability to influence stakeholders, solve complex data challenges, and provide technical leadership in a matrixed environment.

Responsibilities

Lead the design, development, and optimization of enterprise commercial datasets for analytics, reporting, AI, and business operations.
Architect and maintain scalable ETL/ELT pipelines using Alteryx, SQL, Python, and AWS technologies.
Design and evolve dimensional models, master data structures, and curated analytical datasets.
Establish technical standards and best practices for data engineering, data integration, and data integrity across the Analytics CoE.
Partner with business stakeholders, analytics teams, and IT to translate business requirements into scalable, sustainable data solutions.
Implement automation and monitoring solutions to improve pipeline reliability, accuracy, and operational efficiency.
Mentor analysts and provide technical leadership across data engineering, modeling, and data management initiatives.
Incorporate data quality, lineage, and stewardship requirements into enterprise data solutions to support data governance.
Lead root-cause analysis and remediation of complex data issues affecting enterprise reporting and analytics.