Data Engineer implementing data pipelines on Snowflake platform with a focus on innovation and collaboration for Zurich's data projects.
About the role
- Data Engineer developing scalable data products and pipelines for General Motors' advanced analytics. Collaborating with cross-functional teams to ensure robust data systems and predictive insights.
Responsibilities
- Architect and build scalable data pipelines and services using Databricks, Spark, and Azure to support advanced analytics and machine learning workflows.
- Design and implement industrial-grade data products that ingest, transform, and serve vehicle, battery, and environmental data for product health monitoring.
- Collaborate with cross-functional teams to define data requirements and deliver solutions that meet business and technical needs.
- Ensure data quality, integrity, and governance across all stages of the data lifecycle.
- Optimize performance of data systems and pipelines to support real-time and batch processing.
- Develop and maintain documentation, testing frameworks, and CI/CD pipelines for data engineering workflows.
- Demonstrate proficiency in Python through hands-on coding, peer reviews, and technical interviews.
- Support the integration of new data sources and technologies into the platform, ensuring scalability and maintainability.
Requirements
- Master’s degree in Software Engineering, Computer Science, Information Technology, or related field.
- 5+ years of experience in data engineering, software development, or building data-intensive applications.
- Proficiency with Databricks, Spark, SQL, and Python.
- Experience designing and deploying data pipelines in cloud environments (preferably Azure).
- Strong understanding of distributed systems, data modeling, and ETL best practices.
- Ability to translate ambiguous business problems into scalable data solutions.
- Excellent communication and collaboration skills.
- Demonstrated ability to work in a fast-paced, cross-functional environment.
Benefits
- Relocation benefits may be available
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