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Cloud Data Engineer with AI Product Development Expertise
hace 2 meses
Job Overview
Mechanical AI Inc. is seeking a highly skilled Cloud Data Engineer to spearhead the development of cutting-edge AI products across various cloud platforms (Azure, GCP, AWS). The ideal candidate will possess extensive experience in cloud data-focused solutions, particularly in Python and cloud infrastructure.
Responsibilities
- Create end-to-end cloud architectures for data-centric products on Azure, GCP, or AWS.
- Leverage Infrastructure as Code using Pulumi or Terraform to ensure efficient and scalable deployments.
- Develop expertise in authentication best practices (Auth0, Cognito), SQL & NoSQL databases on the cloud, network configuration (NLBs), logging, and data streaming.
- Design and implement multi-tenant and single-tenant platform tools.
- Build products utilizing ECS, Flask, and Python.
- Promote DevOps best practices throughout the development lifecycle.
Requirements
- Minimum 4 years of industry experience as a Cloud Data Engineer/Backend Engineer.
- Demonstrated expertise in Python (4+ years) and Flask (2+ years).
- Bachelor's or Master's degree in Computer Science.
- Experience in Machine Learning or Deep Learning projects that have successfully transitioned to production environments.
- DevOps pipeline experience from scratch, utilizing CodePipeline or equivalents.
- Strong ability to collaborate effectively with front-end team members.
Estimated Salary
The estimated annual salary for this position is approximately $140,000 - $200,000, depending on location and experience.
Preferred Skills
- Experience in managing large-scale data products on the cloud, handling TBs of data, and executing millions of pipeline deployments daily.
- Pyspark (1+ year) expertise.
- Security experience.
- AWS Solution Architect Associate or higher certification (ideal).
- AWS Data Certificates.
- Basic understanding of front-end development, ideally React.
- Experience designing and implementing large dataset architectures; streaming, batch datasets, data lakes, and meshes.
- Expertise in creating data pipelines on the cloud: Glue, EMR, serverless EMR, step functions, Kafka/Kinesis, storage, and equivalents.
