Kranthi kumari Potnuru

Data Scientist

Hyderabad, Telangana, India3 yrs 10 mos experience

Highly Stable

Key Highlights

Designed ADF pipelines reducing manual interventions by 40%.
Optimized PySpark jobs, cutting processing time by 25%.
Achieved 99% data accuracy through automated workflows.

Stackforce AI infers this person is a SaaS Data Engineer specializing in Azure data solutions and ETL processes.

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Skills

Core Skills

Azure Data FactoryEtl WorkflowsAzure Databricks

Other Skills

.NET FrameworkASP.NETASP.NET MVCAzure Data LakeAzure DevOps ServicesAzure Key VaultAzure SQLC (Programming Language)C#C++Cascading Style Sheets (CSS)CommunicationContinuous Integration and Continuous Delivery (CI/CD)Data LoadingData Modeling

About

I am an Azure Data Engineer with 3.5 years of experience in designing, developing, and optimizing data pipelines and ETL workflows using Azure Data Factory (ADF), Databricks, Microsoft Fabric, PySpark, SQL, and Python. At Accenture, Designed and orchestrated Azure Data Factory (ADF) pipelines to enable seamless ingestion and transformation of large-scale enterprise data, improving pipeline reliability and reducing manual interventions by 40%. Developed and optimized PySpark jobs in Databricks to process structured and unstructured datasets (terabytes in size), resulting in a 25% reduction in processing time. Wrote, debugged, and performance-tuned SQL queries across Azure SQL Database and Synapse, ensuring efficient reporting and analytics. Automated ETL workflows and data quality checks, increasing data accuracy to 99% and reducing repetitive support issues. Resolved access, data extract, and pipeline incidents, ensuring uninterrupted delivery for critical business operations. Collaborated with cross-functional teams (business analysts, BI developers, and cloud engineers) to deliver production-ready, scalable, and secure data solutions. Supported migration of legacy pipelines to Azure cloud, enabling cost savings and enhanced scalability. Impact Summary: Delivered scalable and optimized cloud data solutions that empowered enterprise clients to achieve faster insights, higher data reliability, and reduced operational costs. 📌 Currently serving notice period | Immediate Joiner 📍 Open to roles: Azure Data Engineer | Data Engineer | ETL Developer 🌍 Locations: Hyderabad | Bangalore | Pune | Chennai | Remote

Experience

3 yrs 10 mos

Total Experience

3 yrs 2 mos

Average Tenure

8 mos

Current Experience

Ltimindtree

Senior Data Engineer

Oct 2025 – Present · 8 mos · Hyderabad, Telangana, India · Hybrid

Accenture

2 roles

Application Development Analyst

Sep 2024 – Oct 2025 · 1 yr 1 mo · Hyderabad, Telangana, India · Hybrid

Designed and maintained ADF pipelines for data integration and transformation, reducing processing time by 30%.
Developed PySpark scripts in Databricks to process large datasets across structured and unstructured sources.
Optimized SQL queries and ETL workflows, improving data refresh performance.
Automated data quality checks, ensuring 99% reliability in production pipelines.
Collaborated with cross-functional teams to resolve and debug pipelines, and worked on business-critical reporting needs.

Azure Data FactoryPySparkSQLETL workflows

Application Development Associate

Aug 2022 – Sep 2024 · 2 yrs 1 mo · Hyderabad, Telangana, India · Hybrid

Utilized Azure Databricks for complex data transformations and implementations of intricate business logic, optimizing big data processing capabilities.
Troubleshot and resolved issues in Azure Data Factory pipelines, ensuring robust and uninterrupted data flow across the organization's data ecosystem.
Led production support efforts, swiftly addressing pipeline issues and implementing proactive measures to maintain high system availability and performance.
Actively participated in Agile sprint planning and requirement refinement sessions, collaborating with cross-functional teams to align data engineering solutions with business objectives.
Optimized data ingestion, processing, and storage workflows, significantly improving data pipeline efficiency and reducing time-to-insight for business users.
Leveraged Delta Lake tables for efficient data storage and modification, enhancing data reliability and enabling ACID transactions in a distributed environment.
Employed Azure SQL for advanced query operations, data analysis, and reporting, supporting critical business intelligence initiatives.
Collaborated with cross-functional teams to align data engineering solutions with business objectives, driving data-driven decision making across the organization.
Contributed to the development of best practices and standards for data engineering processes, promoting code reusability and maintainability across the team.

Azure DatabricksAzure Data FactorySQLDelta Lake