Data Modeler

Job Description :

Must Have Technical/Functional Skills
• Strong with data modeling concepts (star schemas, snowflake schemas, highly normalized data models).
• Data modeling tools – Erwin.
• Data Warehouse database platforms – Snowflake, BigQuery, Databricks.
• Knowledge and experience of at least one data profiling tool.
• Familiar with ETL tools like DataStage/Informatica.
• Experience with AWS services including S3, Lambda, Data-pipeline, and other data technologies
• Conceptual knowledge of BI tools like Business Objects/Tableau is a plus.
• Deep understanding of principles in data warehousing and cloud architecture with principles of SQL 
optimization for building very efficient and scalable data systems.
• Excellent SQL programming skills.
• Excellent problem solving skills.
• Excellent communication skills with both business and technical customers.
• Demonstrate a high level of integrity and maturity.
• Work on multiple projects and deliver consistently on time.
• Escalate issues appropriately to management and project team.
• Take a proactive approach to cross-functional communication.
• Actively seek out feedback from management and peers, to improve own performance based on that feedback

Roles & Responsibilities

• Interacting with Business Users/ Business Relationship Managers to understand the BI and analytical needs
• Identify the right data sources / data completeness to meet the BI needs.
• Data profiling to build the entity relationships across multiple sources.
• Develop and maintain data dictionary for all the data sources (existing and new ones).
• Build conceptual and logical data models considering the BI needs. 
• Develop optimized database design to achieve acceptable performance by tuning views, tables for proper response time.
• Work with database administrators to implement data models into database platforms, ensuring data integrity 
and consistency.
• Monitor database performance, identify bottlenecks, and optimize data models to improve query efficiency and 
data access speed.
• Work closely with the IT teams in ETL design discussions adopting best practices of data load strategy.
• Identify effective reporting techniques, identify the best data sources for each report, identify risks and constraints,
and design reporting formats.
• Create and maintain metadata describing the data model, including data lineage and definitions. 
• Data analyst skills to determine root cause problems for data integrity and data quality issues identified through QA
or by business report owners.
• Define data storage strategy