Lokesh Verma

Software Engineer

Pune, Maharashtra, India4 yrs 11 mos experience

Highly StableAI ML Practitioner

Key Highlights

Designed and optimized scalable data pipelines.
Led successful cloud migration projects with high uptime.
Certified in multiple data engineering technologies.

Stackforce AI infers this person is a Data Engineering expert with a focus on cloud solutions and scalable data architectures.

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Skills

Core Skills

Data EngineeringCloud ComputingSoftware DevelopmentDevops

Other Skills

Azure DatabricksAzure Data LakePySparkLinuxAzure Data FactoryETLCI/CDCloud MigrationApache SparkDelta LakePythonETL OptimizationAzure DevOps ALMCross-team CollaborationMicrosoft Certified Technology

About

Currently a Data Engineer at Capgemini, holding a Bachelor of Engineering in Computer Science from NIT Nagpur. Earned multiple certifications, including Microsoft Azure Data Engineer Associate and Databricks Certified Data Engineer Associate, reflecting a commitment to professional growth in data engineering. Contributed to the design of efficient data pipelines using Azure Data Factory and Databricks. Implemented cloud migration strategies and CI/CD pipelines, ensuring seamless deployment and collaboration. Skilled in leveraging tools like Unity Catalog and Delta Lake to enhance data management processes.

Experience

4 yrs 11 mos

Total Experience

3 yrs 10 mos

Average Tenure

1 yr 1 mo

Current Experience

Capgemini

Data Engineer

Apr 2025 – Present · 1 yr 1 mo · Pune · Hybrid

Azure DatabricksAzure Data LakeData EngineeringCloud Computing

Tech mahindra

3 roles

Data Engineer

Aug 2021 – Mar 2025 · 3 yrs 7 mos

Designed, developed, and maintained scalable data solutions for generating, collecting, and processing, ensuring optimized ETL pipelines. Led end-to-end ETL workflows using Azure Data Factory (ADF), reducing pipeline runtime by 40% and improving performance. Migrated 15+ critical data pipelines from on-premises to Azure, achieving 99.9% uptime and ensuring a seamless transition. Collaborated with cross-functional teams to understand data requirements and design efficient data solutions. Implemented parameterized and reusable ADF pipelines, enhancing efficiency and minimizing manual intervention. Optimized Apache Spark jobs in Databricks, fine-tuning configurations to minimize resource consumption. Developed a robust, metadata-driven ETL framework leveraging medallion architecture to process 14K+ tables and terabytes of data using Databricks Autoloader, Delta Lake, Python, PySpark, and Apache Spark. Utilized Delta Lake for handling large volumes of incremental data with ACID transactions and time-travel features.

Azure Data FactoryApache SparkDelta LakePythonPySparkData Engineering+1

Senior Software Engineer

Jun 2021 – Apr 2025 · 3 yrs 10 mos

PySparkLinuxData EngineeringSoftware Development

Software Engineer

Jun 2021 – Apr 2025 · 3 yrs 10 mos

Designed ETL jobs using Azure Data Factory (ADF) to enhance data quality and efficiency within data pipelines.
Led the successful on-premises to Azure cloud migration for specific data pipelines in Azure Data Factory (ADF).
Implemented a robust CI/CD pipeline for the deployment of Azure Data Factory code, ensuring seamless collaboration and efficient code management.

Azure Data FactoryETLCI/CDData EngineeringCloud Computing