Work Arrangement
This role is categorized as hybrid. This means the successful candidate is expected to report to Austin, TX, Roswell, GA, or Warren, MI three times per week, at minimum.
The Team:
The Loyalty Analytics and Campaign Enablement team is responsible for curating and providing data solutions to enable the General Motors organization to personalize the customer loyalty experience, drive engagement, and provide a holistic view of the Loyalty and GM Card program health and opportunities.
The team is responsible for both analytics and data strategy, as well as direct implementation of solutions to support General Motors Loyalty and GM Card programs.
The Role:
As a Staff Data Engineer will work as a member of a multi-disciplinary Kanban team of various experience levels and will be responsible for solution design, development, and deployment of data engineering solutions across Cloud Based Solutions ( Azure Databricks / Salesforce CRM-A ).
You will build industrialized data assets and optimize data pipelines in support of Advance Analytic objectives. You will work closely with our forward-thinking Data Scientists, BI Developers, System Architects and Data Architects to deliver value to our vision for the future.
What You'll Do
- Drive adoption of cloud-first technologies and industry-standard Data Engineering practices to accelerate and scale our engineering capabilities.
- Organize and lead delivery of on-premises and cloud-based data solutions as a hands-on practitioner and team lead.
- Adhere to standards and processes to validate, monitor, and support data products that enable our decision science portfolio and data science capabilities. Actively drive standards adoption through pull-request reviews, design reviews, and other mechanisms as a practicing data engineer.
- Collaborate with cross-functional teams, including data governance, security, data architecture, release management, Dev & ML Ops, and infrastructure, to ensure seamless integration and alignment of data engineering initiatives.
- Stay up to date with emerging trends and technologies in the field of Data Engineering, and proactively identify opportunities for improvement and innovation within our organization.
- Participate in a culture of continuous learning, knowledge sharing, and development within the team and the broader data engineering community.
