Assistant Manager- Data Engineering
2 months ago
Key Objectives:
- Design and maintain engineering infrastructure to support enterprise machine learning systems in Azure cloud
- Support model development, following industry best practices on auditability, versioning, and data security
- Facilitate development and deployment of proof-of-concept machine learning solutions
- Collaborate with Data Scientists to take offline machine learning model solutions and deploy them into production systems
- Very good hands-on experience in deploying end-to-end ML solutions as an ML DevOps Engineer or Data Engineer
- Manage stakeholders and drive timely execution of projects using agile methodologies
- Build reliable and scalable solutions in a fast-paced work environment
- Knowledge sharing with other team members on technical skills and best practices
Eligibility Criteria and Functional Competencies Required:
- University degree in Computer Sciences or a similar field of studies
- At least 3 to 5 years of relevant experience in deploying ML solutions into production systems
- Exposure to machine learning frameworks and best practices
- Deep knowledge in Python, T SQL, database systems
- Ability to translate business needs into technical requirements
- Familiarity with data-oriented workflow orchestration frameworks such as AirFlow, KubeFlow, etc.
- Very high data affinity and strong analytical skills
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