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Together with our customers, we're on a mission to make healthcare better.
The Role
Designs, builds, and maintains scalable ETL/ELT pipelines, data models, data marts, and automated workflows for analytics and reporting. Develops SQL and Python, Scala, or Java transformations; supports cloud data platforms; and implements data quality, governance, security, monitoring, and error handling. Collaborates with architects, analysts, platform teams, and business stakeholders to deliver reliable data solutions. Requires 3–5 years of data engineering, ETL, or database development experience.
Summary Generated by Built In
Work Flexibility: Hybrid
The Data Engineer designs, builds, and maintains scalable data pipelines and integration solutions that power analytics, reporting, and business decision-making. This role works closely with Data Architects, Analysts, and Platform teams to ingest, transform, and deliver reliable, high-quality data across the Data and Analytics ecosystem, while following established engineering standards and best practices.
What you will do:
- Design and optimize scalable ETL/ELT pipelines, data models, and data marts to enable reliable analytics and reporting.
- Develop automated data workflows using orchestration tools while building efficient SQL and Python/Scala-based transformation processes.
- Ensure data quality, governance, security, and compliance through robust validation, monitoring, and error-handling frameworks.
- Support cloud data platforms and collaborate with stakeholders to deliver high-performance, business-driven data solutions.
- Strong expertise in data engineering, including batch/streaming processing, SQL, and programming with Python, Scala, or Java.
- Hands-on experience with distributed data frameworks, cloud data platforms, and modern data warehouse/lakehouse technologies.
- Proven ability to troubleshoot complex technical issues, ensure data quality, and deliver reliable, scalable data solutions.
- Collaborative and adaptable professional who works effectively across teams, embraces new technologies, and independently drives results.
What you will need:
Required Skills:
- Bachelor’s degree in Computer Science, Information Systems, Engineering, or a related discipline required with 3-5 years of experience in data engineering, ETL development, or database development.
- Strong proficiency in SQL and hands-on experience with at least one programming language (Python, Scala, or Java).
- Working knowledge of relational databases and data warehousing/lakehouse concepts.
- Ability to analyze complex data requirements and translate them into scalable technical solutions.
- Experience with cloud data platforms such as Snowflake, Databricks, AWS Redshift, or Azure Synapse along with hands on experience in building and maintaining data pipelines on-premises or in a cloud environment.
- Experience with workflow orchestration tools such as Apache Airflow, Azure Data Factory, or dbt. And streaming technologies such as Kafka, Kinesis, or Event Hubs.
- Familiarity with CI/CD practices and version control (Git) for data engineering workflows and understanding of data modeling techniques (dimensional modeling, star schema, data vault)., knowledge of Data Lake, Lakehouse and Unity Catalogue Concepts, use of Tool’s AI features to bring efficiency in Coding and bug fixing
- Cloud platform certification (AWS, Azure, or GCP Data Engineer track) preferred./ Snowflake, Databricks, or equivalent data platform certification preferred
Skills Required
- Bachelor's degree in Computer Science, Information Systems, Engineering, or a related discipline
- 3–5 years of experience in data engineering, ETL development, or database development
- Strong proficiency in SQL
- Hands-on experience with Python, Scala, or Java
- Working knowledge of relational databases and data warehousing or lakehouse concepts
- Ability to analyze complex data requirements and translate them into scalable technical solutions
- Experience with Snowflake, Databricks, AWS Redshift, or Azure Synapse
- Experience building and maintaining data pipelines in on-premises or cloud environments
- Experience with Apache Airflow, Azure Data Factory, or dbt
- Experience with Kafka, Kinesis, or Event Hubs
- Familiarity with CI/CD practices and Git
- Understanding of dimensional modeling, star schema, data vault, data lake, lakehouse, and Unity Catalog concepts
- AWS, Azure, or GCP Data Engineer certification
- Snowflake, Databricks, or equivalent data platform certification
Stryker Compensation & Benefits Highlights
The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about Stryker and has not been reviewed or approved by Stryker.
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Healthcare Strength — Multiple medical plan options with HSA support and global mental‑health access indicate broad, accessible care. These features materially enhance the overall value of the total‑rewards package.
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Retirement Support — A meaningful 401(k) company match with potential additional company contribution, alongside an ESPP, supports long‑term savings and wealth building. Documented plan specifics help employees understand eligibility, timing, and vesting mechanics.
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Parental & Family Support — Paid parental and caregiver leave, adoption and surrogacy assistance, and practical supports like breast milk shipping reflect a comprehensive, family‑friendly approach. These offerings address varied family‑building paths and caregiving needs.
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The Company
What We Do
Stryker is a global leader in medical technologies and, together with its customers, is driven to make healthcare better. The company offers innovative products and services in MedSurg, Neurotechnology, Orthopaedics and Spine that help improve patient and healthcare outcomes. Alongside its customers around the world, Stryker impacts more than 130 million patients annually. More information is available at www.stryker.com. Together with our customers, we are driven to make healthcare better.
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