Principal I, Data Engineering (T)

Summary of Position: At Alcon, we're passionate about enhancing sight and helping people see brilliantly. With more than 25,000 associates, we innovate fearlessly, champion progress, and act swiftly to impact global eye health. We foster an inclusive culture, recognizing your contributions and offering opportunities to grow your career like never before. Together, we make a difference in the lives of our patients and customers. Are you ready to join us? Key Responsibilities: The Principal I, Data Engineering (Science/Tech/Engineering Path), is primarily responsible for managing projects to design and implement scalable data systems using advanced technical skills for impactful solutions. Specifics include: Design, develop, and operationalize reusable, scalable, and modular data and analytics platforms aligned with Alcon’s enterprise architecture to enable efficient, consistent, and automated value generation from data. Lead the design and implementation of end-to-end cloud-native data solutions on AWS, including data ingestion, transformation, orchestration, and consumption layers. Develop and maintain robust, scalable, and high-performance ETL/ELT data pipelines using AWS services such as Glue, Lambda, S3, Step Functions, EventBridge, and related technologies. Design and optimize data warehouse solutions using Amazon Redshift, including schema design, performance tuning, workload management, partitioning, and query optimization. Partner with data architects to define technical architectures, data integration patterns, and best practices for data and analytics products. Design and implement conceptual, logical, and physical data models that support scalable analytics, reporting, and AI/ML use cases. Advise, mentor, and coach data engineering and analytics teams on cloud architecture, data modeling, data governance, data quality, and engineering best practices. Participate in backlog grooming, sprint planning, technical design reviews, and effort estimation activities. Perform data analysis, data profiling, and data modeling to deliver actionable business insights and support strategic decision-making. Evaluate, implement, and deploy emerging data engineering, cloud, and analytics technologies to improve platform capabilities, scalability, and team productivity. Foster a culture of innovation, collaboration, engineering excellence, automation, and continuous improvement. Key Requirements/Minimum Qualifications: Bachelor's degree in Computer Science, Data Science, Engineering, or a related technical discipline. 7+ years of hands-on experience in data engineering, including designing, building, and supporting enterprise-scale ETL/ELT pipelines, data platforms, data lakes, and data warehouse solutions. 5+ years of hands-on experience developing cloud-native data solutions on AWS, including S3, Redshift, Glue, Lambda, IAM, CloudWatch, EventBridge, and related services.