Helping clients solve their most complex and interesting business problems by designing and implementing Google Cloud data and AI solutions
Requirements
- Proven experience as a Cloud Data and AI Engineer or similar role, with hands-on experience in Google Cloud tools and services (e.g., BigQuery, Vertex AI, Dataflow, Cloud Storage, Pub/Sub, etc.).
- Strong knowledge of data engineering concepts, such as ETL processes, data warehousing, data modeling, and data governance.
- Proficiency in AI engineering, including experience with machine learning models, model training, and MLOps pipelines using tools like Vertex AI, BigQuery ML, and AutoML.
- Strong problem-solving and decision-making skills, particularly with large-scale data systems and AI model deployment.
- Experience with agile methodologies and project management tools in the context of Google Cloud data and AI projects.
- Knowledge of security and compliance best practices as they relate to data and AI solutions on Google Cloud.
- Google Cloud certifications (e.g., Professional Data Engineer, Professional Database Engineer, Professional Machine Learning Engineer) or willingness to obtain certification within a defined timeframe.
Responsibilities
- Design, build, and operationalize large-scale enterprise data and AI solutions using Google Cloud services such as BigQuery, Vertex AI, Dataflow, Cloud Storage, Pub/Sub and more.
- Implement cloud-based data solutions for data ingestion, transformation, and storage; and AI solutions for model development, deployment, and monitoring, ensuring both areas meet performance, scalability, and compliance needs.
- Develop and maintain comprehensive architecture plans for data and AI solutions, ensuring they are optimized for both data processing and AI model training within the Google Cloud ecosystem.
- Provide technical leadership and guidance on Google Cloud best practices for data engineering (e.g., ETL pipelines, data pipelines) and AI engineering (e.g., model deployment, MLOps).
- Conduct assessments of current data architectures and AI workflows, and develop strategies for modernizing, migrating, or enhancing data systems and AI models within Google Cloud.
- Stay current with emerging Google Cloud data and AI technologies, such as BigQuery ML, AutoML, and Vertex AI, and lead efforts to integrate new innovations into solutions for clients.
- Mentor and develop team members to enhance their skills in Google Cloud data and AI technologies, while providing leadership and training on both data pipeline optimization and AI/ML best practices.
Other
- Strong communication and collaboration skills to work with cross-functional teams, including data scientists, business stakeholders, and IT teams, bridging data engineering and AI efforts.
- Ability to work in a fast-paced environment, managing multiple Google Cloud data and AI engineering projects simultaneously.
- Bachelor's, Master's, or Ph.D. degree in a relevant field (not explicitly mentioned but implied)
- Meaningful time off and paid holidays, parental leave, 401(k) with a match, a range of choices for highly subsidized health, dental, & vision coverage, adoption and fertility assistance, and short/long-term disability.
- Yearly $350 reimbursement account for any well-being-related expenses, as well as discounted home, auto, and pet insurance.
