Manager, Data Integrity (Onsite)

Alcon Research•Fort Worth, TX

3d•Onsite

About The Position

As Manager, Data Integrity, you will lead the evolution of enterprise data platforms and data solutions that support commercial decision-making across North America. This is an onsite role in Fort Worth, Texas, for a hands-on data engineering leader who takes ownership of complex data challenges and uses analytics, automation, and AI-enabled insights to influence business strategy. You will partner with commercial and technology organizations to build trusted, scalable data assets that deliver measurable business impact. The role leads the design, development, and optimization of enterprise commercial datasets and scalable ETL/ELT pipelines. It also establishes engineering standards, supports data governance and quality, resolves complex data issues, and provides technical leadership and mentorship across data initiatives.

Requirements

Bachelor’s degree or equivalent years of directly related experience; the posting also lists alternatives of high school plus 13 years, associate degree plus 9 years, M.S. plus 2 years, or Ph.D. plus 0 years.
Ability to fluently read, write, understand, and communicate in English.
5 years of relevant experience.
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.
Ability to influence stakeholders, solve complex data challenges, and provide technical leadership in a matrixed environment.

Nice To Haves

Experience in data engineering, analytics engineering, data architecture, data integration, data management, or related technical disciplines.
Experience supporting analytics, business intelligence, Sales Operations, Marketing, or other commercial organizations.

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 foundational data assets, including 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.
Support data governance by incorporating data quality, lineage, and stewardship requirements into enterprise data solutions.
Lead root-cause analysis and remediation of complex data issues affecting enterprise reporting and analytics.