Job Title: Databricks Data Modeller
Location: Mumbai
Experience: 5–8 Years
Employment Type: Full-time
Role Overview
We are looking for an experienced Databricks Data Modeller with 5–8 years of experience in data modelling, data warehousing and modern Lakehouse environments.
The ideal candidate should have strong hands-on experience with Databricks, Delta Lake, SQL, PySpark, dimensional modelling and Lakehouse architecture. The candidate will work closely with data engineers, architects, BI teams and business stakeholders to design scalable and efficient data models for analytics and reporting.
Key Responsibilities
Design and develop conceptual, logical and physical data models based on business requirements.
Design scalable Star Schema and Snowflake Schema data models.
Define fact tables, dimension tables, relationships, keys and business hierarchies.
Design data models within Databricks Lakehouse architecture.
Work with Bronze, Silver and Gold data layers.
Develop and optimize SQL and PySpark-based transformations.
Design and implement Slowly Changing Dimensions (SCD) and historical data management.
Work with Data Engineers to develop efficient ETL/ELT pipelines.
Analyse source systems and define source-to-target mappings.
Ensure data models support reporting, analytics and business intelligence requirements.
Optimize data models and queries for performance and scalability.
Ensure data quality, consistency and integrity across data layers.
Collaborate with business stakeholders to understand data requirements and translate them into technical models.
Maintain data dictionaries, mapping documents and technical documentation.
Identify and resolve data modelling and data quality issues.
Work with technical teams to ensure appropriate data governance and security.
Required Skills & Qualifications
5–8 years of experience in Data Modelling, Data Warehousing or Data Engineering.
Strong hands-on experience with Databricks.
Strong understanding of Delta Lake and Lakehouse architecture.
Excellent knowledge of SQL.
Hands-on experience with PySpark / Apache Spark.
Strong understanding of Star Schema, Snowflake Schema, Fact and Dimension modelling.
Experience with Slowly Changing Dimensions (SCD).
Strong understanding of ETL/ELT concepts.
Experience working with large-volume datasets.
Good understanding of data warehouse and data lake concepts.
Strong analytical and problem-solving skills.
Ability to interact with business and technical stakeholders.