Architect, Data AI-ML

Job Description

Bachelors in computer science, Information Systems, or a related field Minimum of 10+ years of experience in data architecture with a minimum of 1-3 years of experience in healthcare domain Strong hands-on experience with Cloud databases such as Snowflake, Aurora, Google BigQuery etc. Experience in designing OLAP and OLTP systems for efficient data analysis and processing. Strong handson experience with enterprise BI/Reporting tools like (Looker, AWS QuickSight, PowerBI, Tableau and Cognos). A strong understanding of HIPAA regulations and healthcare data privacy laws is a must-have for this role, as the healthcare domain requires strict adherence to data privacy and security regulations. Experience in data privacy and tokenization tools like Immuta, Privacera, Privitar OpenText and Protegrity. Experience with multiple full life-cycle data warehouse/transformation implementations in the public cloud (AWS, Azure, and GCP) with Deep technical knowledge in one. Proven experience working as an Enterprise Data Architect or a similar role, preferably in large-scale organizations. Proficient in Data modelling (Star Schema (de-normalized data model), Transactional Model (Normalized data model) using tools like Erwin. Experience with ETL/ETL architecture and integration (Matillion, AWS GLUE, Google PLEX, Azure Data Factory etc) Deep understanding of data architectures that utilize Data Fabric, Data Mesh, and Data Products implementation. Business & financial acumen to advise on product planning, conduct research & analysis, and identify the business value of new and emerging technologies. Strong SQL and database skills working with large structured and unstructured data. Experienced in Implementation of data virtualization, and semantic model driven architecture. System development lifecycle (SDLC), Agile Development, DevSecOps, and standard software development tools such as Git and Jira Excellent written and oral communication skills to convey key choices, recommendations, and technology concepts to technical and non-technical audiences. Familiarity with AI/MLOps concepts and Generative AI technology.