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:

- Solid 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.

📌 Data Modeller (Indore)
🏢 BCS Consulting
📍 Indore