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.
- 4+ years of programming experience in Python, Scala, or Java, with strong software engineering fundamentals.
- 3+ years of hands-on experience designing, developing, optimizing, and supporting Amazon Redshift-based data warehouse solutions.
- 3+ years of hands-on experience with dimensional data modeling, star and snowflake schema design, data vault methodologies, and analytical data structures.
- 2+ years of experience designing both batch and streaming architectures for real-time or near real-time data ingestion and processing.
- Strong experience building and maintaining scalable data pipelines using technologies such as AWS Glue, Apache Airflow, Kafka, Spark, or equivalent cloud-native services.
- Experience with two or more database technologies (e.g., PostgreSQL, MySQL, MongoDB) and cloud data warehouse platforms (e.g., Amazon Redshift, Snowflake, BigQuery).
- Experience with source control, CI/CD, infrastructure-as-code, and automated deployment practices for data platforms.
- Proficient with business intelligence and data visualization tools such as Tableau and Amazon QuickSight.
- Strong understanding of data quality, data governance, metadata management, lineage, and monitoring practices.
- Thrives in dynamic, cross-functional team environments and demonstrates a collaborative, team-first mindset.
- Passionate problem solver with strong analytical and troubleshooting skills.
- High learning agility and a continuous improvement mindset.
Preferred Qualifications
- Experience in healthcare, digital health, life sciences, or regulated environments.
- Experience with data privacy and security regulations, including HIPAA, GDPR, CCPA, FDA cybersecurity guidance, and security frameworks such as NIST, HITRUST, ISO 27001, and SOC 2.
- Experience with healthcare interoperability standards such as HL7, FHIR, c-CDA, and DICOM.
- Experience with EMR/EHR and PACS integrations.
- Experience with MLOps and AI/ML platforms such as Amazon SageMaker, Vertex AI, or Azure ML.
- Experience building modern data platforms supporting analytics, AI, machine learning, and self-service reporting.
- AWS certifications such as AWS Certified Data Engineer, AWS Solutions Architect, or AWS Analytics Specialty are highly desirable.
Work hours: 1 PM to 10 PM IST
Relocation assistance: Yes
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Alcon is an Equal Opportunity Employer and takes pride in maintaining a diverse environment. We do not discriminate in recruitment, hiring, training, promotion or other employment practices for reasons of race, color, religion, gender, national origin, age, sexual orientation, gender identity, marital status, disability, or any other reason.