Tushar Mali

Azure Data Engineer with 5.3+ years of IT experience, including 4.5+ years of expertise in designing, developing, optimizing, and maintaining enterprise-scale ETL/ELT data pipelines on Microsoft Azure. Extensive experience in Azure Data Factory, Azure Databricks, Microsoft Fabric, dbt, Azure Synapse Analytics, Azure Data Lake Storage Gen2, Azure SQL Database, Delta Lake, and PySpark. Strong experience in building scalable Lakehouse architectures, implementing Medallion Architecture (Bronze, Silver, Gold), developing metadata-driven pipelines, Spark optimization, cloud migration, and incremental data processing.

Proven ability to deliver high-performance, secure, and cost-efficient data solutions supporting business intelligence, advanced analytics, and enterprise reporting. Hands-on experience across Retail and BFSI domains, collaborating with cross-functional teams in Agile environments while ensuring data quality, governance, scalability, and operational excellence.

Senior Data Engineer - The Math Company (MathCo)

(2026-02)

Client: GAP (Retail)

• Write and optimize complex SQL queries for data extraction, transformation, and validation across large-scale retail datasets.
• Develop and maintain Databricks notebooks using PySpark and SQL for processing, cleaning, and enriching retail transactional data
• Build, test, and document dbt models to create standardized, version-controlled, analytics-ready datasets for downstream reporting.
• Implement dbt testing and documentation practices to ensure data quality, consistency, and transparency across transformation layers.
• Configure and maintain CI/CD workflows using GitHub Actions to automate testing, validation, and deployment of dbt models and Databricks jobs.
• Collaborate with cross-functional analytics and business teams in an Agile environment to translate reporting requirements into reliable data pipelines.

System Engineer (Azure Data Engineer role) - Tata Consultancy Services

(2021-04 - 2026-02)

Client: Deutsche Börse Group (BFSI)

• Designed and implemented end-to-end ETL pipelines migrating and consolidating client data from multiple SQL databases into Azure SQL Database using ADF data flows.
• Built and maintained Databricks notebooks for data validation, transformation, and enrichment using PySpark DataFrame APIs.
• Developed scalable Lakehouse architecture in Microsoft Fabric consolidating multiple enterprise data sources.
• Migrated legacy ETL workloads from ADF to Microsoft Fabric.
• Implemented Delta tables in Fabric Lakehouse for ACID transactions and efficient data versioning.
• Applied data partitioning and parallel processing in Databricks to reduce processing time.
• Established data quality checks, lineage tracking, and metadata management in ADF pipelines.
• Monitored and managed Databricks clusters, optimizing cost and performance based on workload patterns.
• Automated pipeline orchestration across ADF, Databricks, and Synapse ensuring seamless data flow.
• Designed alerting mechanisms for pipeline failures and performance anomalies to enable proactive issue resolution.
• Monitored Spark job execution metrics (CPU, memory, shuffle, skew) to identify bottlenecks and optimize workloads.
• Collaborated in Agile environment using Jira for sprint planning, tracking, and delivery.
• Reduced overall data pipeline runtime by 20% through optimized cluster configurations and efficient partitioning.
• Automated multiple manual workflows, saving approximately 7 hours per week for the data engineering team.
• Improved data accuracy and consistency by 20% by implementing standardized validation frameworks in Databricks.

Bachelor of Engineering - Mechanical - Shivaji University

Diploma - Mechanical Engineering - Walchand College of Engineering

SSC - Pandit Nehru Vidyalaya