Data Warehouse Architect

Title – Data Warehouse Architect

Location – Kharadi, World Trade Center, Pune

Experience Range – 15 Years

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Roles & Responsibilities:

• Data Warehouse Design: Define the architecture and structure of the data warehouse, including data models, schemas, and data integration processes.
• Data Modeling: Develop data models (e.g., star schema, snowflake schema) to optimize data storage and retrieval for reporting and analysis.
• ETL (Extract, Transform, Load): Design and oversee the implementation of ETL processes to extract data from source systems, transform it to meet business needs, and load it into the data warehouse.
• Data Integration: Ensure data from various sources (databases, applications, APIs) is integrated seamlessly into the data warehouse.
• Performance Optimization: Continuously monitor and optimize the data warehouse’s performance to ensure efficient query processing and data retrieval. 
• Data Quality Assurance: Implement data quality checks and validation processes to maintain data accuracy and consistency within the data warehouse. 
• Security and Access Control: Establish security protocols and access controls to protect sensitive data within the data warehouse, ensuring compliance with data privacy regulations. 
• Scalability and Growth: Plan for the scalability of the data warehouse to accommodate future data growth and evolving business requirements. 
• Documentation: Maintain comprehensive documentation of the data warehouse architecture, data flows, and transformation processes. 
• Collaboration: Work closely with business analysts, data analysts, and data engineers to understand data requirements and translate them into data warehouse solutions. 
• Vendor Evaluation: Evaluate and recommend data warehousing tools and technologies, such as data warehouse platforms (e.g., Snowflake, Amazon Redshift, Azure Synapse Analytics), ETL tools, and BI tools. 
• Performance Tuning: Identify and resolve performance bottlenecks, optimizing query performance and system efficiency. 
• Disaster Recovery and Backup: Implement strategies and plans for data warehouse backup, disaster recovery, and business continuity. 
• Data Governance: Enforce data governance and data management best practices to maintain data quality, lineage, and compliance.

Must Skills : 

• Data Modeling: Develop data models (e.g., star schema, snowflake schema) to optimize data storage and retrieval for reporting and analysis. 
• ETL (Extract, Transform, Load): Design and oversee the implementation of ETL processes to extract data from source systems, transform it to meet business needs, and load it into the data warehouse. 
• Data Integration: Ensure data from various sources (databases, applications, APIs) is integrated seamlessly into the data warehouse. 
• Performance Optimization: Continuously monitor and optimize the data warehouse’s performance to ensure efficient query processing and data retrieval. 
• Data Quality Assurance: Implement data quality checks and validation processes to maintain data accuracy and consistency within the data warehouse. 
• Security and Access Control: Establish security protocols and access controls to protect sensitive data within the data warehouse, ensuring compliance with data privacy regulations. 
• Scalability and Growth: Plan for the scalability of the data warehouse to accommodate future data growth and evolving business requirements. 
• Documentation: Maintain comprehensive documentation of the data warehouse architecture, data flows, and transformation processes. 
• Collaboration: Work closely with business analysts, data analysts, and data engineers to understand data requirements and translate them into data warehouse solutions. 
• Vendor Evaluation: Evaluate and recommend data warehousing tools and technologies, such as data warehouse platforms (e.g., Snowflake, Amazon Redshift, Azure Synapse Analytics), ETL tools, and BI tools. 

Good to have skills  

• Big Data Technologies: Familiarity with big data technologies such as Hadoop, Hive, and HBase can be valuable. 
• Cloud Services: Knowledge of cloud platforms like AWS, Azure, or Google Cloud can be essential, as many organizations are moving their data warehousing solutions to the cloud for scalability and cost-effectiveness. 

​​Qualifications and Education Requirements​ 

• Bachelor’s degree in computer science, information technology, or a related field. 
• Proven experience as an DW Architect or similar role.