Shaik Imran Basha

Design and develop scalable ETL/ELT pipelines using PySpark, Databricks, Azure Data Factory, AWS Glue, and Airflow.

• Build modern Data Lakehouse solutions using Medallion Architecture (Bronze, Silver, Gold layers).

• Develop data ingestion frameworks from enterprise data sources such as MySQL, SAP HANA, Teradata, APIs, JSON, CSV, and Parquet files.

• Design and optimize Spark-based data processing workloads using partitioning, caching, broadcast joins, and performance tuning techniques.

• Implement cloud-native data solutions using Azure, AWS, Databricks, Snowflake, and DBT Cloud.

• Develop dimensional data models, fact tables, dimension tables, and KPI reporting datasets for analytics and business intelligence.

• Build workflow orchestration solutions using Airflow, Azure Data Factory, Databric

Design and develop scalable ETL/ELT pipelines using PySpark, Databricks, Azure Data Factory, AWS Glue, and Airflow.
Build enterprise Data Lakehouse solutions using Medallion Architecture (Bronze, Silver, Gold layers).
Develop and optimize big data processing frameworks using Spark, Delta Lake, and cloud-native services.
Implement data ingestion pipelines from multiple enterprise systems such as MySQL, SAP HANA, Teradata, APIs, and streaming platforms.
Design data models, fact and dimension tables, and analytics datasets for reporting and KPI dashboards.
Work with Snowflake and DBT Cloud for modern cloud data warehouse implementations and ELT transformations.
Optimize query performance, Spark jobs, partitioning strategies, and cloud resource utilization.
Build workflow orchestration pipelines using ADF, Airflow, Databricks Workflows, and cloud-native schedulers.
Collaborate with business, analytics, and AI teams for enterprise reporting and predictive analytics solutions.

Design and develop scalable ETL/ELT pipelines using PySpark, Databricks, Azure Data Factory, AWS Glue, and Airflow.
Build enterprise Data Lakehouse solutions using Medallion Architecture (Bronze, Silver, Gold layers).
Develop and optimize big data processing frameworks using Spark, Delta Lake, and cloud-native services.
Implement data ingestion pipelines from multiple enterprise systems such as MySQL, SAP HANA, Teradata, APIs, and streaming platforms.
Design data models, fact and dimension tables, and analytics datasets for reporting and KPI dashboards.
Work with Snowflake and DBT Cloud for modern cloud data warehouse implementations and ELT transformations.

Design and develop scalable ETL/ELT pipelines using PySpark, Databricks, Azure Data Factory, AWS Glue, and Airflow.
Build enterprise Data Lakehouse solutions using Medallion Architecture (Bronze, Silver, Gold layers).
Develop and optimize big data processing frameworks using Spark, Delta Lake, and cloud-native services.
Implement data ingestion pipelines from multiple enterprise systems such as MySQL, SAP HANA, Teradata, APIs, and streaming platforms.
Design data models, fact and dimension tables, and analytics datasets for reporting and KPI dashboards.
Work with Snowflake and DBT Cloud for modern cloud data warehouse implementations and ELT transformations.