Sarang Deshmukh

I’m an Azure Data Engineer with 3 years of experience designing and optimizing large-scale cloud data pipelines on Microsoft Azure. At Tech Mahindra (Client: AT&T), I process 100M+ records/month across multi-vendor geospatial and address datasets for the LQP (Location Qualification Provisioning) platform.

I build robust ETL/ELT pipelines and data lakehouse solutions using Python, PySpark, SQL, Azure Data Factory (ADF), Azure Databricks, Azure Synapse Analytics, and Delta Lake on ADLS Gen2. I architect Medallion (Bronze–Silver–Gold) lakehouses, implement incremental ingestion and SCD Type 1 & 2 using Delta Lake merge (upsert), and enforce data quality with schema validation, null checks, deduplication, and referential integrity.

I’m hands-on with Spark performance tuning (partition pruning, broadcast joins, Adaptive Query Execution (AQE), and Delta table compaction with OPTIMIZE + ZORDER) and I orchestrate 15+ ADF pipelines with weekend/off-hours triggers, activity chaining, retry policies, and Azure Monitor alerts for SLA compliance. I also led recovery and restoration of a mission-critical environment, earning a Standing Ovation Award, and I’m now seeking senior data engineering roles in product-based or consulting environments.