Vishal Mahendar

Software Engineer

5 yrs 10 mos experience

AI EnabledAI ML Practitioner

Key Highlights

Built a Real-Time Fraud Detection Lakehouse.
Led migration of banking data platforms to Azure.
Developed scalable ETL/ELT pipelines for enterprise data.

Stackforce AI infers this person is a Data Engineering expert in Fintech and Cloud Data Solutions.

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Skills

Core Skills

Data EngineeringAzure DatabricksReal-time Data ProcessingAzure Data FactorySql

Other Skills

Azure FabricETL/ELT pipelinesPySparkDelta LakeMedallion ArchitectureGreat ExpectationsAzure Event HubsDatabricks Structured StreamingTerraformAzure DevOpsAzure Synapse AnalyticsData ModelingPower BIETL pipelinesSSIS

About

Data Engineer with 5+ years of experience working with enterprise applications, data systems, and cloud technologies. Skilled in building scalable ETL/ELT pipelines, real-time data processing solutions, and data platforms using PySpark, Databricks, Azure Data Factory, SQL, Python, and Delta Lake. Experienced in data modeling, data warehousing, batch and streaming pipelines, and optimizing large-scale data workflows. Recently built a Real-Time Fraud Detection Lakehouse using PySpark Structured Streaming and Delta Lake to process and analyze transaction data in near real time. Passionate about transforming raw data into meaningful insights, solving complex data challenges, and building reliable, scalable data solutions that drive business value.

Experience

5 yrs 10 mos

Total Experience

2 yrs 3 mos

Average Tenure

1 yr 4 mos

Current Experience

Pnc

Senior Data Engineer

Feb 2025 – Present · 1 yr 4 mos · Dallas, TX · Remote

Designed and implemented Azure Databricks and Azure Fabric-based data lakehouse solutions to integrate and process large-scale enterprise data.
Built scalable ETL/ELT pipelines using Azure Data Factory, PySpark, and Delta Lake, enabling efficient batch and near real-time data processing.
Implemented Medallion Architecture (Bronze, Silver, Gold) to improve data quality, governance, and scalability across analytics platforms.
Developed data validation frameworks using Great Expectations, improving data accuracy and reliability for downstream reporting and analytics.
Built real-time streaming pipelines using Azure Event Hubs and Databricks Structured Streaming to process high-volume event data.
Automated infrastructure provisioning and deployment processes using Terraform and Azure DevOps CI/CD pipelines.
Optimized data processing performance through partitioning, query tuning, and Databricks workload optimization, improving efficiency and reducing operational costs.
Collaborated with cross-functional teams to deliver scalable data solutions that supported business intelligence, reporting, and data-driven decision-making.

Azure DatabricksAzure FabricETL/ELT pipelinesPySparkDelta LakeMedallion Architecture+6

Capgemini

Data Engineer

Jan 2021 – Jan 2023 · 2 yrs · Bengaluru · Hybrid

Led the migration of enterprise banking data platforms from on-premises systems to Azure cloud environments using Azure Data Factory and Azure Synapse Analytics.
Developed scalable data ingestion and transformation pipelines using Azure Data Factory, Azure Databricks, PySpark, and SQL to process transactional, customer, and financial data.
Designed and optimized data models and partitioned tables in Azure Synapse Analytics to support high-performance analytics and reporting workloads.
Built and maintained ETL/ELT workflows to automate data movement, transformation, and integration across multiple data sources.
Developed Python-based data validation and reconciliation frameworks to improve data quality, consistency, and operational efficiency.
Implemented real-time data processing solutions using Azure Event Hubs to support near real-time analytics and reporting.
Integrated Power BI dashboards with enterprise datasets to deliver actionable business insights and performance metrics.
Automated infrastructure provisioning and deployment processes using Terraform and Azure DevOps, improving consistency across environments.
Optimized query performance, data partitioning, and indexing strategies, reducing data latency and improving overall system efficiency.
Collaborated with business, analytics, and engineering teams to deliver secure, scalable, and reliable cloud-based data solutions.

Azure Data FactoryAzure Synapse AnalyticsPySparkSQLData ModelingPower BI+3

Flipkart

ETL Developer

Jun 2018 – Dec 2020 · 2 yrs 6 mos · Bengaluru · On-site

Developed and maintained ETL pipelines for e-commerce data, including customer, sales, inventory, and product analytics datasets.
Designed and implemented data transformation workflows using SSIS, Informatica, SQL Server, and Azure Data Factory.
Built SQL Server data marts to support reporting, business intelligence, and analytical initiatives across multiple business functions.
Migrated legacy ETL workflows to Azure Data Factory, improving scalability, reliability, and operational efficiency.
Automated ETL scheduling, monitoring, and alerting processes using Control-M, reducing manual effort and improving workflow management.
Collaborated with business stakeholders to define data mappings, transformation logic, and reporting requirements.
Implemented data validation and quality assurance processes to ensure data accuracy, consistency, and completeness across data pipelines.
Supported Azure SQL Data Warehouse migration initiatives and contributed to the modernization of enterprise data platforms.
Optimized ETL processes and database performance, improving data availability and reporting efficiency.
Worked closely with analytics and reporting teams to deliver reliable data solutions that supported business decision-making.