General Motors - Boston, MA
posted 2 months ago
The Marketing Applied Sciences team at General Motors is dedicated to developing analytics-driven solutions that empower GM organizations to achieve their business objectives. As a Data Engineer, you will be an integral part of a multi-disciplinary team, collaborating with various experience levels to design, develop, and deploy analytic models that support business-facing analytic groups. This team is tasked with both advanced analytics strategy and applied, project-based solutions, focusing on the company's most critical business areas. Your role will involve building analytical data sets that support Advanced Analytics projects, working closely with innovative Researchers and Data Scientists to deliver value aligned with GM's vision for the future. This position reports to the Product Owner of Marketing Activation Science and has visibility within the broader Enterprise Data, Analytics, and Insights organization, which is focused on democratizing data and decision-making across the company. In this role, you will collaborate with internal and external stakeholders, including Activation Data Science, to deliver on the project portfolio. You will drive the adoption of cloud-first technologies and industry-standard Data Engineering practices to enhance and scale engineering capabilities. Adhering to established standards and processes, you will validate, monitor, and support data products that enable the decision science portfolio and data science capabilities. Collaboration with cross-functional teams, including data governance, security, data architecture, release management, Dev & ML Ops, and infrastructure, will be essential to ensure seamless integration and alignment of data engineering initiatives. Staying current with emerging trends and technologies in Data Engineering will allow you to proactively identify opportunities for improvement and innovation within the organization. You will also participate in a culture of continuous learning, knowledge sharing, and development within the team and the broader data engineering community.