Data Modeller

Role & responsibilities

• Enterprise Data Architecture & Modeling: Lead the design, development, and maintenance of Conceptual, Logical, and Physical data models for both OLTP and OLAP enterprise systems.
• Dimensional Modeling & Warehousing: Architect scalable Data Warehouse schemas using Kimball methodology, facts, dimensions, star, and snowflake schemas to support advanced analytics.
• Database & Cloud Optimization: Design robust relational and cloud database structures across platforms such as Oracle, SQL Server, PostgreSQL, Snowflake, Amazon Redshift, and Azure Synapse.
• Data Modeling Tool Mastery: Utilize industry-standard tools (ERwin, ER/Studio, SAP PowerDesigner, Oracle SQL Developer Data Modeler, Lucidchart, or Visio) to generate and maintain comprehensive data models and documentation.
• ETL/ELT Integration & Pipeline Design: Collaborate with data engineering teams to define data pipelines, source-to-target mappings (STM), ETL/ELT workflows, and transformation logic.
• Data Governance & Metadata Management: Establish data modeling standards, maintain enterprise business glossaries, manage metadata, and enforce Data Governance and Master Data Management (MDM) best practices.
• Cross-Functional Collaboration: Partner with BI developers, cloud architects, and business analysts in an Agile/Scrum environment to ensure data models align with reporting and business intelligence requirements (Power BI, Tableau, Looker).
• Cloud & Advanced Tech Integration: Leverage cloud data ecosystems (Azure, AWS, GCP) and big data platforms (Databricks, Spark) to modernize data pipelines and support NoSQL/API integrations where required.

Preferred candidate profile

• Experience: 7 to 10 years of overall IT experience with a minimum of 3 years of hands-on expertise in enterprise data modeling (OLTP & OLAP).
• Core Technical Expertise:
• Strong mastery of Conceptual, Logical, and Physical Data Modeling using Kimball Dimensional Modeling methodologies.
• Deep expertise in writing complex SQL queries and designing relational and dimensional databases.
• Tools & Platforms:
• Data Modeling Tools: Proficiency in ERwin, ER/Studio, SAP PowerDesigner, Oracle SQL Developer Data Modeler, Lucidchart, or Visio.
• Databases & Cloud Warehouses: Hands-on experience with Oracle, SQL Server, PostgreSQL, MySQL, Snowflake, Amazon Redshift, or Azure Synapse.
• Cloud Ecosystems: Working knowledge of cloud platforms (AWS, Azure, or GCP).
• Process & Governance Knowledge: Solid grasp of Data Warehousing, ETL/ELT concepts, Metadata Management, Master Data Management (MDM), Data Governance, and Agile/Scrum practices.
• Good-to-Have Skills (Preferred):
• Exposure to Big Data & Lakehouse platforms like Databricks, Apache Spark, or PySpark.
• Experience with ETL/ELT tools (Informatica, Talend, Azure Data Factory, Fivetran).
• Familiarity with BI tools (Power BI, Tableau, Looker) and Data Governance frameworks (Microsoft Purview, Collibra, Alation).
• Basic knowledge of NoSQL databases (MongoDB, Cassandra, DynamoDB) and REST APIs.
• Relevant Cloud Certifications (AWS, Azure, or GCP) are a strong plus.