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• Corp-Corp

• Contract to Hire

• Consulting/Contract

• UG :- - Not Required

• PG :- - Not Required

• No of position :- ( 1 )

• Post :- 14th Feb 2023

·       Strong understanding of data modeling concepts and methodologies (e.g. dimensional, relational, semantic)

·       Knowledge of data warehousing design patterns and dimensional modeling techniques

·       Extensive experience with data warehousing, OLAP (Online Analytical Processing), big data, and cloud technologies

·       Strong proficiency in SQL and NoSQL databases – Oracle, PostgreSQL and Redshift

·       Ability to design and implement complex data models to support business requirements that align with reporting and analytics

·       Proficiency in SQL and data modeling tools (e.g. ER Studio, ERWin)

·       Good understanding of data governance and data management best practices

·       Strong ability to analyze and interpret large amounts of data

·       Excellent communication skills to effectively collaborate with cross-functional teams and stakeholders

·       Ability to stay up to date with new trends and technologies in the data modeling field

·       Strong understanding of data architecture concepts, models, and frameworks

·       Ability to translate complex technical concepts into business terms

·       Knowledge of ETL (Extract, Transform, Load) processes using Talend

·       Strong knowledge of data security and privacy best practices

·       Understanding of data visualization and reporting tools (e.g. PowerBI, QuickSight)

·       Strong problem-solving and critical thinking skills

Job Duties-

·       Design and implement optimized data models to support business requirements

·       Develop and maintain a data dictionary and metadata repository

·       Collaborate with cross-functional teams to understand business requirements and translate them into data models

·       Ensure data models are accurate, consistent, and support data governance and data management best practices

·       Develop and maintain relationships with data owners and stakeholders to ensure data models meet their needs

·       Perform data profiling and analysis to understand data quality and completeness

·       Ensure data models are optimized for performance and scalability

·       Participate in data architecture design and implementation efforts

·       Stay up to date with new trends and technologies in the data modeling field

·       Document data models and data architecture artifacts

·       Collaborate with cross-functional teams, such as software engineers, to integrate data solutions into the overall technology stack

·       Troubleshoot and resolve data-related issues and failures in the production environment.

·       Build Source-To-Target mapping documents to enable data engineers to build data pipelines

·       Implement data security and privacy controls

·       Monitor and optimize the performance of data pipelines