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Cherrish M
@cherrishmiddha
Azure Databricks and Microsoft Fabric Data Engineer
India
Sobre mí
Technical Lead Data Engineer with 4+ years building production data platforms on Azure, Databricks and Microsoft Fabric. I build lakehouses (bronze/silver/gold) with PySpark, Delta Lake, Azure Data Factory and Snowflake. Highlights: Spark jobs processing 5TB+ daily, 30% faster; 15+ ADF pipelines moving 1.2M+ records a day; a metadata-driven Fabric framework that cut onboarding effort by 70%; SharePoint to Fabric (OneLake) ingestion. I can build new pipelines, migrate legacy ETL, or speed up slow Spark jobs. Message me with your data sources and goal.
Habilidades
Cherrish M
desconectado •
Tiempo medio de respuesta: 1 hora
Revisa mis servicios
ETL de datos
I will build azure data factory and databricks etl pipelines
Consultoría de ingeniería de datos
I will optimize and speed up your slow pyspark and databricks jobs
Experiencia laboral
Technical Lead
Trianz • Tiempo completo
Jul 2026 - Present • 4 mos
Lead Databricks data engineering delivery for a US real-estate investment client. Unified properties, leases and deals across 5+ source systems into one master ID per record. Built a Databricks lakehouse using PySpark and Delta Lake. Designed config-driven Databricks jobs and guided the team on pipeline design and code quality.
Senior Data Engineer
DecisionTree Analytics • Tiempo completo
Oct 2025 - Jun 2026 • 8 mos
Designed a metadata-driven ingestion framework in Microsoft Fabric for dynamic pipeline execution. Developed Snowflake stored procedures for metadata tracking using SCD logic. Automated metadata ingestion using information_schema, cutting onboarding effort by 70%. Built parameterized pipelines for multi-environment deployment.
Data Engineer
WNS Global Services • Tiempo completo
Apr 2023 - Sep 2025 • 2 yrs 5 mos
Built scalable Spark jobs in Databricks processing 5TB+ of data daily, reducing runtime by 30%. Developed 15+ Azure Data Factory pipelines handling 1.2M+ records per day. Created a PySpark validation framework maintaining 99.8% accuracy and optimized SQL queries to improve reporting performance by 56%.
