Data Modelling - Pune

Only for registered members Pune, India

1 day ago

Default job background
₹900,000 - ₹2,200,000 (INR) per year *
* This salary range is an estimation made by beBee
5 to 8 years of data modelling experience in a large enterprise. Dimensional data modeling is a key requirement. · Should be good at translating business requirements into conceptual, logical, and physical data models. · Knowledge of Star-Schema Modelling, Snowflake Schema Modell ...
Job description
  • 5 to 8 years of data modelling experience in a large enterprise. Dimensional data modeling is a key requirement.
  • Should be good at translating business requirements into conceptual, logical, and physical data models.
  • Knowledge of Star-Schema Modelling, Snowflake Schema Modelling, Fact, and Dimension tables.
  • Demonstrable experience in modeling using a variety of techniques (3NF, dimensional, data vault, etc.) for different data stores and use cases using MS SQL SERVER / SNOWFLAKE.
  • Implement business and IT data requirements through new data strategies and designs across all data platforms (relational, dimensional, and NoSQL) and data tools (reporting, visualization, analytics).
  • Work with business and application/solution teams to implement data strategies, build data flows, and develop conceptual/logical/physical data models
  • Define and govern data modeling and design standards, tools, best practices, and related development for enterprise data models.
  • Identify the architecture, infrastructure, and interfaces to data sources, tools supporting automated data loads, security concerns, analytic models, and data visualization.
  • Design and implement reliable, scalable, robust, and extensible big data systems that support core products and business;
  • Own all data modeling efforts for an Analytic Theme within our Snowflake Analytic Platform, including the design of data structures and the identification of business transformation logic.
  • Ensure the consistency, availability, understanding, and performance of data by following and improving best practices and standards for data modeling.
  • Partner with data SMEs, data governance staff and architects and product owners to ensure that data meets consumption needs and conforms to governance standard methodologies.


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