The Role
Build and maintain scalable data pipelines, integrations, and transformations in cloud-based environments. Translate stakeholder requirements into data engineering solutions, support data architecture and movement, document data assets, and improve data quality, performance, scalability, and automation. Collaborate cross-functionally to deliver data-driven outcomes and communicate technical findings through reports, presentations, and visualizations.
Summary Generated by Built In
Work Flexibility: Remote
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.
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
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.
Skills Required
- 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 another data-related discipline
- 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 with object-oriented programming concepts and data structures
- Knowledge of ETL/ELT development, data modeling, data warehousing, and distributed data processing
- 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 tools and cloud-native data architectures
- Experience optimizing data pipelines, workflows, and distributed computing environments for performance and scalability
Inari Medical Compensation & Benefits Highlights
The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about Inari Medical and has not been reviewed or approved by Inari Medical.
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Fair & Transparent Compensation — Pay is considered competitive for many roles, with employees described as 'extremely happy' with total compensation including pay, stock, equity, and benefits. Feedback suggests above‑average salary levels across departments contribute to strong pay sentiment.
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Healthcare Strength — Benefits include comprehensive medical, dental, and vision coverage, with 100% employer‑paid premiums for employees cited in multiple descriptions. Additional options like critical illness, accident, hospital indemnity, and wellness programs reinforce the healthcare offering.
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Leave & Time Off Breadth — Time off is characterized by unlimited PTO, cited as a top benefit by employees. Paid holidays and flexible hours are also referenced, expanding the range of time‑off options.
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The Company
What We Do
Inari Medical, Inc. is a commercial-stage medical device company focused on developing products to treat and transform the lives of patients suffering from venous diseases.
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