GEN AI Data Architect

GEN AI Data Architect Location: Noida, UP, India Job Description PRIMARY RESPONSIBILITIES Articulate and document a data architecture solution vision Develops conceptual, logical, and physical data models, and supports the development of data strategies by building roadmaps and creating processes to meet current and future needs Develop data frameworks and scalable approaches to support an evolving data architecture and integration needs that can be leveraged and re-used for new data-driven business products, services, and functions Provides recommendations on innovative data platforms, tools and services, and aligns decision-making with the organization''s strategic data vision and all standard policies, processes, and procedures Develop and implement cloud data platforms to support product strategy and roadmap, advanced analytics, data science and SQL/NO-SQL datasets to give business, products, and operations a competitive advantage Oversees data architecture designs, business requirements, prototypes, testing, and training Provide strategic recommendations for technology adoption to improve productivity, collaboration, and efficiency Ensure data architecture and practices comply with relevant industry standards and regulations, such as GDPR, HIPAA, and CCPA Establish and enforce data quality standards and practices Adhere to ethical standards and comply with the laws and regulations applicable to your job function Manages a repository of documentation related to data architecture standards, protocols, and frameworks, and regularly evaluates for improvement opportunities Regularly review and update architecture documentation to reflect changes in technology and business needs Maintain the technology catalog and manage the technology adoption process Maintains currency with emerging technologies, leveraging industry knowledge and expertise to drive continuous improvement and innovation efforts in data architecture and related areas (e.g., APIs, LLMs, GenAI, Microservices, Event-based architectures) Continuously improve processes, technologies, and platforms to provide best value to business Identify cost-savings opportunities through the optimization of existing tools Facilitate cross team and cross component collaboration Technical Expertise: Strong expertise in Azure Analysis Services (AAS), Power BI Premium Gen2, Azure Data Factory, Azure Synapse, Data/Delta Lake, Microsoft Fabric, and Data Pipelines. Proven experience in designing and implementing data solution on the Azure Platform Experience with cloud data platforms (e.g., AWS, Azure, Google Cloud) and data warehousing solutions (e.g., Redshift, BigQuery, Snowflake). Strong knowledge of SQL and experience with relational databases (e.g., Oracle, PostgreSQL, SQL Server). Experience with Pyspark framework building data lake (S3/Iceburg), data warehouse (on Redshift Serverless/Spectrum), EMR (serverless), pipelines catalogs construction (Glue, Athena) Experience with NoSQL databases (e.g., DynamoDB, Cassandra) and big data technologies (e.g., Hadoop, Spark). Understanding of ETL processes and tools (e.g., Python). o Knowledge of data governance, data quality, and data security practices Mandatory Competencies Data Science and Machine Learning - Data Science and Machine Learning - Gen AI BI and Reporting Tools - BI and Reporting Tools - Power BI Cloud - Azure - Azure Data Factory (ADF), Azure Databricks, Azure Data Lake Storage, Event Hubs, HDInsight Cloud - AWS - Tensorflow on AWS, AWS Glue, AWS EMR, Amazon Data Pipeline, AWS Redshift Cloud - Cloud - Snowflake Big Data - Big Data - Pyspark Data Science and Machine Learning - Data Science and Machine Learning - Apache Spark Data Science and Machine Learning - Data Science and Machine Learning - Databricks Data Science and Machine Learning - Data Science and Machine Learning - Python Database - Database Programming - SQL Cloud - AWS - AWS SNS, AWS SQS, AWS Kinesis Beh - Communication and collaboration