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The Data Engineer will manage and engineer data projects within GCP, handling data ingestion, storage, analysis, and migration from legacy systems, while collaborating with teams to meet data requirements.

The AI/ML Engineer will analyze diverse data sources, create machine learning models, and communicate insights to clients, ensuring effective data-driven decision-making.

Lead data management and engineering projects using AWS, focusing on data migration, analysis, and designing data solutions while collaborating with technical teams and ensuring data quality.

The role involves leading enterprise-scale migrations from Microsoft 365 to Google Workspace, architecting solutions, and providing pre-sales consulting for AI-driven workflows.

The Site Reliability Engineer ensures system reliability, creates automation, advises on DevOps practices, and collaborates with clients and engineers to resolve issues in cloud environments.

The Data Architect will design and manage cloud-based data architectures on Azure and GCP, focusing on data modeling, governance, and performance optimization.

The Data Analytics Architect will design and implement data solutions using Looker, collaborate with stakeholders, and mentor junior staff, translating business needs into technical strategies.

The Systems Administrator maintains security, stability, and automation in a hybrid environment, managing Windows and Linux systems, GCP infrastructure, and utilizing automation tools for efficiency.

Lead a security operations team, oversee incident response workflows, and implement threat detection strategies while managing security infrastructure.

The Cloud Data Engineer will design, build, and maintain data platforms using Snowflake and Azure Databricks, ensuring scalability and optimization. Responsibilities include creating ETL pipelines, providing technical support, and overseeing multi-cloud integrations for clients.