Senior Staff Data Engineer

Stryker is a healthcare technology company focused on supporting clinical, device, and commercial data domains. The Senior Staff Data Engineer will shape enterprise data architecture, build scalable data platforms and reusable data products, lead complex data engineering initiatives, and establish secure, governed, high-performing data ecosystems.

Responsibilities:

• Define and evolve enterprise data architecture patterns across Azure and Databricks environments
• Establish scalable data ingestion, transformation, and modeling frameworks supporting multi-domain data
• Drive platform decisions related to performance optimization, scalability, and cost efficiency
• Lead the design and implementation of reusable data assets and data products that enable self-service analytics
• Own end-to-end delivery of complex data engineering initiatives from requirements through deployment
• Design and implement data pipelines supporting healthcare data sources including EHR, registries, imaging, robotics, telemetry, and patient-reported outcomes
• Define and implement data governance, lineage, cataloging, and access-control frameworks while supporting privacy and compliance requirements
• Provide technical leadership, mentor data engineering teams, and contribute to engineering standards and continuous improvement initiatives

Requirements:

• Bachelor's degree in Computer Science, Data Analytics, Mathematics, Statistics, Data Science, or a related field
• Minimum 6 years of related data engineering and architecture experience
• Experience with Databricks, including Delta Lake and Unity Catalog, and Azure data services such as Azure Data Factory, Synapse, and ADLS Gen2
• Experience designing scalable data architectures using medallion or lakehouse patterns
• Experience with distributed data processing technologies, including Spark, SQL, and Python
• Experience architecting and optimizing large-scale ETL/ELT pipelines, orchestration frameworks, and performance tuning solutions
• Experience implementing data governance, metadata management, lineage, and data quality frameworks
• Knowledge of healthcare data, clinical datasets, privacy regulations, and compliance requirements