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DATA · Data-Engineering

Senior Staff Data Engineer

Stryker

Senior · 6+ yrsRemote · USFull Time$118000–255700Listed 1mo ago
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Experience Senior · 6+ yrs (6+ years)

About the role

structured by ORI

Work Flexibility: Remote Join a team focused on building scalable, enterprise-grade data platforms that support complex healthcare, clinical, device, and commercial data domains. In this role, you will shape modern data architecture strategies, develop reusable data products, and help establish secure, governed, and…

What you will do

  • 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.

What they are looking for

  • 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.

Nice to have

  • 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.
AzureDatabricksDelta LakeUnity CatalogAzure Data FactorySynapseADLS Gen2SparkPythonSQL
Full posting text

Work Flexibility: Remote Join a team focused on building scalable, enterprise-grade data platforms that support complex healthcare, clinical, device, and commercial data domains. In this role, you will shape modern data architecture strategies, develop reusable data products, and help establish secure, governed, and high-performing data ecosystems using cloud-based technologies.

What You Will Do

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.

What You Will Need

Required Qualifications

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.

Preferred Qualifications

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.

USN : $118,000 - $196,700 USD Annual

US5 : $123,900 - $206,500 USD Annual

US10 : $129,800 - $216,400 USD Annual

US15 : $135,700 - $226,200 USD Annual

US20 : $141,600 - $236,000 USD Annual

US30 : $153,400 - $255,700 USD Annual

View the U.S. work location and transparency guide to find the pay range for your location.

Travel Percentage: 10% Stryker Corporation is an equal opportunity employer. Qualified applicants will receive consideration for employment without regard to race, ethnicity, color, religion, sex, gender identity, sexual orientation, national origin, disability, or protected veteran status. Stryker is an EO employer – M/F/Veteran/Disability. Stryker Corporation will not discharge or in any other manner discriminate against employees or applicants because they have inquired about, discussed, or disclosed their own pay or the pay of another employee or applicant.

However, employees who have access to the compensation information of other employees or applicants as a part of their essential job functions cannot disclose the pay of other employees or applicants to individuals who do not otherwise have access to compensation information, unless the disclosure is (a) in response to a formal complaint or charge, (b) in furtherance of an investigation, proceeding, hearing, or action, including an investigation conducted by the employer, or (c) consistent with the contractor’s legal duty to furnish information.

Originally posted on Himalayas

Data-EngineeringData-ArchitectureSenior-Data-EngineeringCloud-Data-Platform-EngineeringHealthcare-Data-EngineeringData-EngineerStaff-Data-EngineerSenior-Lead-Data-EngineeringSenior-Data-Engineer-Positions
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Opportunity details

Deadline
Closing in 14d · 7 Nov

As stated by the source. Anything not shown was not stated.

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