> Markdown version of [/jobs/ext/4409134-principal-data-engineering](https://www.wearedevelopers.com/jobs/ext/4409134-principal-data-engineering). Every page supports `.md` or `Accept: text/markdown`. Links point to the HTML versions so they work for humans too. Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md).

---

# Principal, Data Engineering

- **Company:** Alcon Inc
- **Location:** Edgecliff Village, TX, United States
- **Experience:** Expert
- **Contract:** Permanent contract
- **Skills:** Training Data, Artificial Intelligence, Data Analysis, Application Frameworks, Cloud Computing, Data as a Services, Data Architecture, Information Engineering, Machine Learning, Power BI, Enterprise Data Management, Data Ingestion, Generative AI, Data Analytics, Data Pipelines
- **Published:** October 26, 2026
- **Apply:** https://www.indeed.com/viewjob?jk=ea2084ce9d80e5ab

## About the Role

* Bachelor's Degree or Equivalent years of directly related experience (or high school +13 yrs; Assoc.+9 yrs; M.S.+2 yrs; PhD+0 yrs)
 * The ability to fluently read, write, understand, and communicate in English
 * 5 Years of Relevant Experience

Preferred Qualifications:

 * Power BI
 * Business intelligence

## Description

We foster an inclusive culture and are looking for diverse, talented leaders to join Alcon. The Principal Data Engineer is a senior technical leader responsible for designing, building, and evolving scalable, reliable, and secure enterprise data platforms and data products.

This role provides hands-on technical leadership across data architecture, data pipelines, cloud platforms, data quality, governance, and engineering practices. The Principal Data Engineer partners closely with Data Science, BI/Analytics, product teams, business stakeholders, and technology teams to ensure trusted, well-engineered data is available for analytics, AI, machine learning, reporting, and operational use cases.

The role is intended to be a technical leadership position rather than a people-management position, with significant responsibility for architecture decisions, engineering standards, mentoring, and solving the organization's most complex data engineering challenges.

In this role, a typical day will include:

Technical Leadership & Architecture

 * Serve as a technical leader for enterprise data engineering solutions.
 * Design scalable data architectures, data pipelines, integration patterns, and reusable data services.
 * Establish engineering standards for data ingestion, transformation, storage, orchestration, testing, monitoring, and deployment.
 * Lead technical design reviews and guide teams toward scalable solutions rather than short-term fixes.
 * Evaluate emerging data technologies and recommend practical adoption where they provide measurable value.

Data Pipeline Engineering

 * Design and develop robust batch and streaming data pipelines across enterprise data sources.
 * Build reusable frameworks that improve development speed, consistency, observability, and maintainability.
 * Optimize data pipelines for performance, scalability, reliability, and cost.
 * Establish monitoring and alerting to proactively identify pipeline and data-quality issues.
 * Improve pipeline reliability, freshness, and data-quality outcomes, which are specifically identified as engineering measures in your current organization material.

AI & Analytics Enablement

 * Partner with Data Scientists and analytics teams to create reliable, AI-ready data foundations.
 * Develop data pipelines and curated datasets supporting machine learning, forecasting, optimization, Generative AI, and advanced analytics.
 * Support production AI solutions through appropriate data architecture, lineage, quality controls, monitoring, and reusable data services.
 * Work closely with ML/AI engineering teams to enable scalable model development and deployment.