About The Role We are looking for a highly skilled Data Modeller with strong expertise in Databricks and modern data engineering practices. The candidate will be responsible for designing scalable data models, implementing dimensional modeling techniques, and building efficient data pipelines using the Medallion architecture. Key Responsibilities Design and implement scalable data models (Star Schema / Snowflake Schema) Build and manage dimension and fact tables with SCD Type 1 & Type 2 handling Develop and optimize data pipelines using Databricks (PySpark / SQL) Implement Medallion Architecture (Bronze, Silver, Gold layers) Perform data cleansing, transformation, and standardization Optimize Delta Lake tables using partitioning, Z-Order, and performance tuning Collaborate with business and analytics teams to understand data requirements Ensure data quality, governance, and lineage tracking Work on large-scale structured and semi-structured datasets Required Skills Strong experience in Data Modeling (Dimensional Modeling, Data Warehousing concepts) Hands-on experience with Databricks (Delta Lake, Unity Catalog) Strong SQL and PySpark skills Experience in implementing SCD Type 2 using MERGE operations Knowledge of Medallion architecture (Bronze/Silver/Gold) Understanding of data partitioning and performance optimization Experience with handling large-scale datasets Good to Have Experience with Azure (ADF, ADLS, Synapse) Knowledge of CDC (Change Data Capture) pipelines Exposure to API-based data ingestion Experience in Education / Government domain (preferred) What We Are Looking For Strong problem-solving and analytical thinking Ability to design reusable and scalable data models Hands-on approach (not just theoretical knowledge) Experience working in fast-paced data engineering environments Skills: pyspark,medallion architecture,databricks