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The DevOps Engineer will manage cloud infrastructure, develop CI/CD pipelines, and ensure system reliability using tools like Datadog, Terraform, and Kubernetes while collaborating with AI teams.

Design and deploy scalable machine learning models, analyze data, and improve model performance in a collaborative environment.

Lead high-impact AI/ML projects in the automotive domain, overseeing technical strategy, project execution, and client management, while mentoring junior team members.

Design and maintain conceptual, logical, physical, and semantic data models and architectures for enterprise analytics. Establish modeling standards, semantic layers, KPIs, and governed consumption patterns; partner with engineering, BI, governance, and business teams to implement scalable lakehouse and data warehouse solutions supporting reporting, self-service analytics, and AI/ML use cases.

The Senior Cloud Engineer will design and manage AWS cloud infrastructure, collaborate on architectural design, implement security measures, and automate processes using IAC, while supporting development teams with scalable solutions.

The Senior Machine Learning Engineer will design and deploy ML models, analyze large datasets using PySpark, and collaborate across teams in a cloud environment.

Design and maintain scalable ETL/ELT pipelines, develop data solutions using Databricks and Snowflake, and collaborate with cross-functional teams to ensure data quality and performance optimization.

Lead large-scale digital transformation programs, manage cross-functional teams, develop project charters, and drive organizational change management strategies.

Lead design, deployment, and administration of a global multi-tenant Snowflake platform. Implement security, scalability, performance tuning, automation, CI/CD, networking (PrivateLink/VPC), integrations (Okta, AD, Tableau, JDBC), disaster recovery, and collaborate with cross-functional teams to support data products and operations.

The Data Engineer will design and implement scalable data pipelines, build data infrastructure, ensure data quality, and collaborate with teams for analytics and compliance.