Senior Data Engineer improving General Motors vehicle data pipelines, monitoring, and observability. Supporting reliable fleet software operations across Oshawa and Markham hybrid offices.
About the role
- Databricks Data Engineer modernizing a Canadian enterprise data platform for reporting, analytics, and AI initiatives. Building scalable lakehouse pipelines, integrations, and transformations.
Responsibilities
- Design, develop, and maintain data pipelines within the Enterprise Data Platform (EDP)
- Build and optimize ETL/ELT processes for data ingestion, transformation, and integration
- Use an Agentic approach to development and ensure outputs match development standards
- Develop scalable and reusable data solutions using Databricks and cloud-based data technologies
- Support migration and modernization from HANA environments to a modern data platform
- Collaborate with Data Architects on scalable data models and platform solutions
- Develop data transformation logic and workflows for business and analytics requirements
- Ensure data quality, integrity, consistency, and performance
- Troubleshoot data-related issues, bottlenecks, and performance concerns
- Participate in code reviews, testing, deployment, and release activities
- Work with business and analytics teams to understand requirements and deliver fit-for-purpose solutions
- Contribute to platform best practices, documentation, and continuous improvement initiatives
Requirements
- At least 3+ years of hands-on Databricks development experience
- 4+ years of overall Data Engineering, ETL, or Data Integration experience
- Strong experience building ETL/ELT data pipelines and transformation processes
- Proven experience working with large and complex datasets
- Experience developing data solutions within cloud-based platforms
- Solid understanding of data warehousing, data lake, and lakehouse concepts
- Experience working in Agile delivery environments
- Strong problem-solving and analytical skills
- Excellent communication and collaboration abilities
- Experience with Databricks, ETL/ELT development, data engineering, data integration, SQL, Python, data pipeline development, data transformation, and data warehousing concepts
- Experience with Agentic frameworks and AI-assisted coding is a value add
- Preferred: experience supporting large data platform initiatives, significant data migrations, Azure Data Services, Databricks Lakehouse architecture, modern data engineering frameworks, AI/GenAI/Machine Learning/advanced analytics, enterprise or consulting environments, data governance, metadata management, and data quality frameworks
- Preferred technical knowledge: Azure Data Factory, Delta Lake, Spark/PySpark, Azure Synapse, data lake architecture, cloud data platforms, data governance and data quality, and CI/CD for data solutions
- Applicants must state their work authorization in Canada
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