Qualifications:

• 10 years of experience in Data Warehousing, Data modeling, Database design.
• Should have worked in designing & building cloud-based data warehouses, databases and data models in Azure, Databricks.
• Should have worked in data modelling tools such as Erwin, ER Studio, etc.
• Should have proficiency in data modelling for transactional, Operational reporting, and analytical solutions (EDW, Data Lake)
• Should have strong hands-on experience writing complex SQL analytical queries (T-SQL, Spark SQL)
• Should have strong hands-on experience in optimizing the data models, SQL queries, databases for performance and scalability.
• Should have in depth knowledge of designing data models using data in Databricks, Azure Synapse, Azure SQL, SQL Server.
• Nice to have knowledge of: Azure Data Factory, SSIS, Azure Functions, Logic Apps, Azure Event Hubs, PySpark, Spark Streaming, ADLS Gen2, Azure Blob, and Tableau.
• Should have worked with Agile methodology.
• Should have worked on handling Batch, Event & Streaming data.
• Should have experience in re-modeling of legacy application databases.
• Should have excellent communication, client-facing, problem-solving skills
• Should have working experience in a global delivery model
• Should have experience in working with product managers, project managers, business users, applications development team members, DBA teams and Data Governance team on a daily basis to analyze requirements, design, development and deployment technical solutions

Responsibilities:

• Collaborate with stakeholders to understand business requirements and translate them into data models that support data-driven decision-making and business objectives.
• Design, develop, and maintain conceptual, logical, and physical data models that accurately represent the organization's data assets.
• Evaluating existing data systems and ensure data models facilitate interoperability and data exchange across disparate systems and platforms.
• Implement best practices for data modeling, including normalization, denormalization, and optimization techniques to ensure data integrity and efficiency.
• Work closely with database administrators and developers to implement data models into database systems efficiently.
• Perform database performance tuning and optimization to enhance performance and scalability.
• Partner with data engineering teams to define allowable table structures, naming conventions, and schema design.
• Ensure data models comply with data governance policies, standards, and regulations.
• Collaborate with data governance teams to establish data modeling standards, processes, and

ensure data models comply with data governance policies, standards, and regulations.

• Develop data integration strategies and solutions to enable seamless data flow between systems and applications.
• Collaborate with cross-functional teams including data scientists, business analysts, solution architects, and DevOps engineers, to deliver end-to-end data solutions that meet business requirements.
• Analyze the different source systems, profile data, understand, document & fix Data Quality issues
• Create design documents, Source to Target Mapping documents and any supporting documents needed for deployment/migration
• Support team during troubleshooting & debugging defects & bug fixes, business requests, environment migrations & other adhoc requests
• Document best practices, code base, and share knowledge