Data Modeller

2 weeks ago


Chennai, Tamil Nadu, India Tata Consultancy Services Full time
Greetings from TCS

Job Title: Data Modeller - Data modelling for OLTP and OLAP systems(Big Query,SQL,BI (Power BI/Tableau/Google PLX
Experience Range: 8 -10 Years

Virtual Drive : 22 Feb 25

Minimum Qualification:

15 years of full-time education

Job Description
Primary Skill
Data modelling for OLTP and OLAP systems
Secondary Skill
Data Warehouse

:
Data Modeller - Hands-on data modelling for OLTP and OLAP systems. In-Depth knowledge of Conceptual, Logical and Physical data modelling. Strong understanding of Indexing, partitioning, data sharding with practical experience of having done the same.Strong understanding of variables impacting database performance for near-real time reporting and application interaction. Should have working experience on at least one data modelling tool, preferably DBSchema.People with functional knowledge of the mutual fund industry will be a plus. Good understanding of GCP databases like AlloyDB, CloudSQL and BigQuery.

Responsibilities:
Designs the overall OLAP data warehouse structure, including dimension tables and fact tables, optimizing for analytical queries
Database Design: Expertise in relational, dimensional, and NoSQL database models.
Data Modeling Tools: Proficiency with data modeling tools like ER diagramming software and GCP-specific data modeling features.
Cloud Computing Knowledge: Understanding of GCP architecture, services like BigQuery, Cloud Spanner, Cloud SQL, and data pipelines.
SQL and Data Manipulation: Strong SQL skills to query and manipulate data within the cloud environment.
Data Governance and Security: Awareness of data governance best practices and cloud security measures.
Communication and Collaboration: Ability to effectively communicate technical concepts to both technical and non-technical stakeholders.
Work closely with data engineers to translate business requirements into technical data models.
Utilize GCP data modeling tools like BigQuery Data Definition Language (DDL) to create and manage data models.
Leverage Cloud Dataflow and other data pipeline services to efficiently load and transform data into the designed data models.
Planning, Developing, and implementing skills that represent the organization's objectives

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