Senior data engineer (remote)

Work Flexibility: Remote

As a Senior Data Engineer on Stryker’s Customer Intelligence Data Engineering team, you will provide tactical execution and delivery of projects within the data engineering project portfolio. You will also help with requirements gathering for new data transformations, build ETL pipelines based on user/project requirements, and develop data dictionaries and other documentation needs for data assets.

What You Will Do:

• Translate business and stakeholder needs into scalable data engineering and data science solutions.
• Partner with cross-functional teams to understand requirements, prioritize opportunities, and deliver data-driven outcomes.
• Communicate technical concepts, project updates, and analytical findings to business and technical stakeholders through presentations, reports, and visualizations.
• Apply data engineering best practices to solve complex business problems and support decision-making.
• Gather, document, and refine business and technical requirements for data products, platforms, and solutions.
• Create and maintain technical documentation for data assets, pipelines, systems, and processes.
• Support the design and implementation of data architecture, data movement, and integration solutions that enable business growth and operational efficiency.
• Contribute to continuous improvement initiatives focused on data quality, performance, scalability, and automation.

What You Need:

Required Qualifications

• Bachelor's degree in Computer Science, Data Engineering, Data Analytics, Mathematics, Statistics, Data Science, Information Systems, or a related field.
• Minimum 2 years of professional experience in data engineering, data architecture, analytics engineering, or other data related disciplines.
• Experience developing and maintaining data pipelines, data integrations, and data solutions in cloud-based environments.
• Proficiency in at least one core data engineering language such as Python, SQL, or Spark.
• Experience working with object-oriented programming concepts and data structures.
• Knowledge of ETL/ELT development, data modeling, data warehousing, and distributed data processing.

Preferred Qualifications

• Master's degree or PhD in Computer Science, Data Science, Engineering, Statistics, Mathematics, or another quantitative discipline.
• Experience with Apache Spark, Databricks, Power BI, or similar analytics and big data technologies.
• Knowledge of infrastructure as code (IaC) tools and cloud-native data architectures.
• Experience optimizing data pipelines, workflows, and distributed computing environments for performance and scalability.

United States of America Pay Ranges:

• USN: $89,300 - $148,800 USD Annual
• US5: $93,800 - $156,200 USD Annual
• US10: $98,200 - $163,700 USD Annual
• US15: $102,700 - $171,100 USD Annual
• US20: $107,200 - $178,600 USD Annual
• US30: $116,100 - $193,400 USD Annual

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

Travel Percentage: 20%

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.