Data Architect

Job Description : To effectively evaluate resumes for the role of "Data/AI Architect", focus on the following core technical skills and experiences. This list includes detailed skills and knowledge areas relevant to the job description provided: Core Technical Skills : 1. AI System Design and Development : - Expertise in deep learning frameworks such as TensorFlow and PyTorch. - Experience with neural network architectures including CNNs and RNNs. - Ability to evaluate and optimize AI architectures for performance, scalability, and efficiency. 2. Data Platform Architecture : - Proficiency in Snowflake architecture and cloud services (Azure, Google Cloud Platform). - Experience designing and implementing scalable, high-performance data monetization platforms. - Strong knowledge of developing and maintaining cloud-based architectures. - Experience with Data Policies, Data Monetization SaaS & APIs, and handling Bigdata (Peta Bytes). 3. MLOps and Automation : - Experience establishing end-to-end MLOps pipelines. - Familiarity with automation tools for model validation, deployment, and maintenance. - Proficiency with ELT solutions and tools such as Docker, Kubernetes, and Jenkins. 4. Data Integration and Management : - Experience with real-time data processing pipelines (Kafka, Airflow, DBT, Snow Pipe, and Snowflake Streams). - Expertise in integrating, metering, and distributing data from various sources. - Skills in efficient data pipelining and management of large datasets (Peta Bytes). 5. Security and Compliance : - Knowledge of data security practices and compliance with industry regulations (HIPAA). - Experience implementing robust security measures and data access controls. - Ability to deploy and configure tools for monitoring and reporting on operational efficiencies. 6. Collaboration and Leadership : - Proven ability to work closely with data scientists, software engineers, and stakeholders. - Leadership skills in guiding cross-functional teams and providing strategic guidance. - Experience translating business needs into technical solutions. 7. Research and Innovation : - Keeping abreast of emerging technologies and industry trends. - Experience with comprehensive audits of AI tools and practices. - Background in experimenting with new tools and frameworks to enhance AI and data solutions. Preferred Skills and Experience : 8. Healthcare Domain Expertise : - Strong understanding of healthcare domain challenges, terminology, and regulations (HL7, HIPAA, FHIR). - Experience working with electronic health records (EHRs) and healthcare data. 9. Certifications and Recognitions : - Relevant certifications in AI, deep learning, MLOps, and Snowflake. - Research contributions such as publications, patents, or significant AI projects in healthcare. 10. Leadership and Mentorship : - Leadership skills with the ability to mentor teams. - Experience driving AI adoption across the organization. (ref:hirist.tech)

Location: hyderabad, IN

Posted Date: 11/23/2024