Senior Staff Data Engineer
New
S
StrykerHealthcare Data
United StatesFull-TimeStaff
Salary118,000 - 255,700 USD per year
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Job Details
- Experience
- Minimum 6 years of related data engineering and architecture experience.
- Required Skills
- PythonSQLETLAzureSparkData modelingDatabricks
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.
- Experience with 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.
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.
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