Senior Data Engineer

General Motors is a company committed to leading change towards a safer, more equitable world. The Senior Data Engineer role focuses on designing and maintaining data infrastructure to support marketing strategies through effective data collection and analysis.

Responsibilities:

• Develop accurate, consistent analytical datasets to support advanced data science and business intelligence initiatives
• Evaluate business requirements, identify relevant data sources, and create datasets that enable actionable insights
• Profile and assess data quality to ensure alignment with business objectives and analytical needs
• Integrate and transform data from multiple sources, building scalable and optimized data pipelines
• Maintain comprehensive metadata, logical models, and data dictionaries for all analytical assets
• Act as the subject matter expert (SME) for analytical datasets, providing guidance and resolving inquiries from data scientists
• Design and implement process improvements, including automation, data delivery optimization, and infrastructure scalability
• Collaborate with business and technology partners to address data-related issues and define infrastructure requirements
• Ensure data quality, security, and compliance with governance and privacy regulations
• Lead and mentor team members and contract resources, driving best practices and educating peers on emerging technologies

Requirements:

• Bachelor's degree in Computer Science, MIS, Software Engineering, or a related field
• 5 - 7+ years of data engineering/development experience, including Python or Scala, SQL, and relational/non-relational data storage. (ETL frameworks, big data processing, NoSQL)
• 3+ years of experience as a data engineer or in a similar role
• 3+ years of experience in distributed data processing (Spark) and container orchestration (Kubernetes)
• Proficiency in data streaming in Kubernetes and Kafka
• Experience with cloud platforms – Azure preferred; AWS or GCP also considered
• Solid understanding of CI/CD principles and tools
• Familiar with predictive / analytical modeling techniques, theories, principles, and practices
• Strong understanding of performance optimization techniques such as partitioning, clustering, and caching
• Proficiency with SQL, key-value datastores, and document stores
• Familiarity with data architecture and modeling concepts to support efficient data consumption
• Strong collaboration and communication skills; ability to work across multiple teams and disciplines
• Master's degree in Computer Science, MIS, Software Engineering, or related field
• Knowledge of data governance, metadata management, or data quality/observability
• Familiarity with schema design and data contracts
• Experience handling various file formats
• Experience with Databricks, Snowflake, or similar platforms
• Experience designing and implementing robust data ingestion frameworks for heterogeneous data sources (structured/unstructured files, external files)