A Staff Data Engineer operates as a recognized expert in data engineering with strong cross-functional visibility.
Lead complex initiatives that improve GM’s data platforms, cloud architecture, and AI-enablement capabilities.
Design and deliver scalable, secure, cloud-native data solutions.
Build highly automated, performant pipelines.
Enable advanced analytics and machine learning use cases across the enterprise.
Design and evolve scalable, high-performance data architectures.
Design ML models and enable AI/ML use cases.
Lead the design and implementation of large-scale data pipelines and data architectures.
Establish organization-wide best practices for data quality, lineage, observability, security, and CI/CD operations.
Architect and optimize solutions on cloud platforms such as Azure, AWS, or GCP.
Partner with data scientists, analysts, and executive stakeholders to translate complex business requirements into technical roadmaps.
Mentor engineers and raise technical capability across the organization.

Bachelor’s degree in Computer Science, Information Systems, Data Science, Business Analytics, Engineering, or a related field; or equivalent experience.
8–10+ years in data engineering or related technical leadership roles
Strong expertise in Python, SQL, Scala, or R with a focus on large-scale data processing, optimization, and performance tuning.
Extensive experience with big data frameworks such as Azure Databricks, Apache Spark, Kafka, or Hadoop for large-scale data processing.
Deep knowledge of cloud platforms and data services such as Azure, AWS, or GCP.
Strong command of data modeling, relational and NoSQL databases, and scalable storage design.
Strong understanding of data governance, privacy, and security controls for enterprise data systems.
Demonstrated ability to lead large-scale technical initiatives and align engineering outcomes to broader business goals.
Strategic thinking with the ability to align technical solutions to GM business priorities.
Strong communication and stakeholder management across technical and non-technical audiences.
Advanced problem solving, architectural judgment, and continuous learning mindset.

Staff Data Engineer – AI, Cloud

Key skills