Iris Software is seeking a GEN AI Data Architect in Dadri, Uttar Pradesh, India. This role involves articulating data architecture vision, overseeing designs, and implementing cloud data platforms. Ideal candidates will have strong expertise in Azure services and proven experience in data solution design. The position offers a dynamic environment with opportunities to improve processes and technologies within data architecture. Strong data science skills are also essential for success in this role.
Qualifications
Proven experience in designing and implementing data solutions on the Azure Platform.
Experience with cloud data platforms (e.g., AWS, Azure, Google Cloud) and data warehousing solutions.
Strong understanding of ETL processes and tools.
Responsibilities
Articulate and document data architecture solution vision.
Oversee data architecture designs and testing.
Regularly review and update architecture documentation.
Skills
Azure Analysis Services (AAS)
Power BI Premium Gen2
Azure Data Factory
Azure Synapse
Data/Delta Lake
SQL
Python
Pyspark
Tools
AWS
Google Cloud
Snowflake
NoSQL databases
Databricks
Job description
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
Big Data - Big Data - Pyspark
Cloud - Cloud - Snowflake
Data Science and Machine Learning - Data Science and Machine Learning - Apache Spark
Data Science and Machine Learning - Data Science and Machine Learning - Databricks
Database - Database Programming - SQL
Data Science and Machine Learning - Data Science and Machine Learning - Python