AWS Tech Lead

• Strong full stack developer background
• Experience with AngularJS
• Familiarity with Java
• Ui Development experience

•Should have 7+ years of experience in handling architecting, designing, and implementing the complex data warehousing and Data Lake and data migration solutions end-to-end.
• Functional experience in Health Care Logical Data Model and aware of how Healthcare manufacturing business work and worked on LENS, Magellan and AISphere products .
• As a Lead Architect facilitate techno-functional design workshops & project implementation involving AWS Architecture, Data Architecture (Data modelling LDM & PDM) & Big data Architecture, Data Engineering Architecture (Python, Spark etc), Data Visualisation tools like Tableau, Power BI, Spotfire, ETL/ELT tools (Glue, Informatica and Teradata ELT tools).
• Data Management experience in large projects implementing end to end solutions for Data Architecture, Data Quality (Trillium, Owl DQ), Data Governance (Collibra) , Data Pipeline, and Master Data Management for various big clients.
• Hands-on experience in AWS Cloud, Big Data Lake, Data Visualization, Artificial Intelligence (AI), Agile BI, Mobile BI, Open data
• Very good experience as an MLOPS architect in a data science project and very good exposure in the AWS Sage maker and experience in deriving Machine learning use-cases starting from proposal, development, testing and productionizing the Models in AWS.
• Work with business product owners, application teams, infrastructure team, vendors, data scientists to conduct Proof of Concepts (POCs), jointly evaluate and implement various data analytics and AI related solutions.
• Establishing and enforcing standards, processes, frameworks, tools and best practices for process modelling, semantic modelling, and logical and physical data modelling.
• Participate in the customer’s strategy meetings to discuss on design, build and maintenance of corporate data architecture, data management standards and conventions, data dictionaries and data element naming standards, classification, and conventions for multiple computing environments.
• Research and evaluate alternative solutions and recommend the most efficient and cost-effective data related solutions for improved data integrity in AWS