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Senior GCP Engineer with Vertex AI and MLOps - Remote (US)

Work from home Full-time role Hiring

Senior GCP Engineer with Vertex AI and MLOps Remote (Cincinnati, OH) Contract Required:

  • Senior GCP engineer with atleast 7 years on project experience.
  • Worked with Vertex AI and ML/Ops.
  • Can work independently with the data science team.
  • Overall Communication needs to be good.

Description:

  • As a Sr. Data Engineer, you will have the opportunity to lead the development of innovative data solutions, enabling the effective use of data across the organization.
  • You will be responsible for designing, building, and maintaining robust data pipelines and platforms to meet business objectives, focusing on data as a strategic asset.
  • A strong emphasis will be placed on expertise in GCP, Vertex AI, and advanced feature engineering techniques.

Key Responsibilities:

  • Provide Technical Leadership
  • Build and Maintain Data Pipelines: Design, build, and maintain scalable, efficient, and reliable data pipelines to support data ingestion, transformation, and integration across diverse sources and destinations, using tools such as Kafka, Databricks, and similar toolsets.
  • Drive Digital Innovation: Leverage innovative technologies and approaches to modernize and extend core data assets, including SQL-based, NoSQL-based, cloud-based, and real-time streaming data platforms.
  • Implement Feature Engineering: Develop and manage feature engineering pipelines for machine learning workflows, utilizing tools like Vertex AI, BigQuery ML, and custom Python libraries.
  • Implement Automated Testing: Design and implement automated unit, integration, and performance testing frameworks to ensure data quality, reliability, and compliance with organizational standards.
  • Optimize Data Workflows
  • Mentor Team Members
  • Draft and Review Documentation: Draft and review architectural diagrams, interface specifications, and other design documents to ensure clear communication of data solutions and technical requirements.
  • Cost/Benefit Analysis: Present opportunities with cost/benefit analysis to leadership, guiding sound architectural decisions for scalable and efficient data solutions

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