Nadipena Venkata Sagar

DevOps Engineer

Bengaluru, Karnataka, India4 yrs 11 mos experience

Highly Stable

Key Highlights

Expert in building robust ETL pipelines on Azure.
Proven track record in optimizing data solutions.
Strong focus on data quality and business decision support.

Stackforce AI infers this person is a Data Engineering expert in cloud-based solutions, specializing in Azure technologies.

Contact

sagarnadipana@gmail.com LinkedIn

Skills

Core Skills

Etl PipelinesDatabricksDelta LakeData ModelingPower BiAzure Data Factory

Other Skills

Adobe XDAzure Data LakeAzure SQLAzure synapseCore JavaETL processesFigma (Software)Microsoft AzureMySQLSQL AzureSQL Server Management StudioSpark SQLVisual Studio

About

Hi, I’m Venkata Sagar, an experienced Azure Data Engineer with 4+ years of hands-on experience designing and deploying cloud-based data solutions on Azure. I specialize in building robust ETL pipelines using ADF, Databricks, Spark, and Delta Lake, enabling seamless data movement from raw ingestion to actionable insights. I’ve contributed to multiple enterprise projects — from migrating legacy SQL workloads to Databricks to optimizing Power BI datasets and automating dashboard refreshes for real-time visibility. I focus on simplifying complex data problems, improving data quality, and building scalable solutions that directly support business decision-making. Currently looking to bring my skills to a forward-thinking team where I can continue solving impactful data engineering challenges. Skills Cloud & Tools: Azure Data Factory (ADF), Databricks, ADLS, Synapse, Power BI, Azure SQL Languages: SQL, PySpark, Spark SQL, Scala Data Engineering: ETL pipelines, Delta Lake, SCD Type 2, data modeling, metadata-driven design Optimization: Legacy migration, cost reduction, dashboard automation Collaboration: Agile, CI/CD, debugging, stakeholder coordination

Experience

Publicis sapient

Senior Associate Data Engineering

Sep 2025 – Present · 6 mos · Bengaluru, Karnataka, India · Hybrid

Pwc india

2 roles

Senior Associate

Promoted

Apr 2025 – Sep 2025 · 5 mos

Associate

May 2024 – Apr 2025 · 11 mos

→ Migrated legacy SQL Server stored procedures and ETL processes to Databricks, using Spark SQL for improved performance and scalability.
→ Validated and optimized legacy stored procedures for compatibility with Databricks and Spark SQL.
→ Developed custom ETL logic to integrate SSIS packages into Databricks notebooks, streamlining data flow.
→ Automated and managed Databricks data pipelines, ensuring schema alignment with legacy systems and maintaining efficient workflows.
→ Built an Insights Platform using Delta Lake architecture to enhance inventory and procurement management and support data-driven decision-making.
→ Designed full-load and incremental loading processes for SAP data, optimizing daily ingestion workflows.
→ Created data models and end-to-end workflows from source systems to Power BI for seamless reporting.
→ Developed a metadata-driven ingestion framework to automate the entire ETL process.
→ Automated the generation of six Power BI dashboards for real-time visualization of client KPIs, supporting quick business decisions.

DatabricksSpark SQLETL processesPower BIDelta LakeETL pipelines

Capgemini

3 roles

Associate Consultant

Jan 2024 – May 2024 · 4 mos

→ Developed a product from scratch using the best practices provided by the client.
→ Improved and optimized a product, reducing infrastructure costs by nearly 7,000 euros, which lowered the overall infrastructure cost by 7%.
→ Optimized cube models by moving them to Power BI datasets, cutting processing time from 8 hours to 4 hours, improving efficiency by 20%.
→ Served as the primary point of contact (SPOC) for three out of five products, handling impact analysis based on requirements.
→ Worked with cross-functional teams to develop and maintain data models for efficient querying and reporting using Azure SQL databases.

Power BIAzure SQLETL pipelinesData modeling

Senior Software Engineer

Promoted

Jan 2023 – Feb 2024 · 1 yr 1 mo

→ Created and updated ETL pipelines in Azure Data Factory (ADF) using Linked Services, Datasets, and Pipelines to extract, transform, and load data from various sources like Azure SQL, Blob Storage, Azure SQL Data Warehouse, and other tools.
→ Developed JSON scripts to deploy pipelines in ADF that process data using SQL activities.
→ Worked on Spark SQL notebooks to extract, transform, and aggregate data from different file formats, helping to analyze and uncover insights into customer usage patterns.
→ Conducted regression testing on live objects after every deployment to ensure there is no impact on the architecture or performance.
→ Reviewed the current production state of the application and assessed how new implementations might affect existing business processes.
→ Investigated production issues, performed root cause analysis of defects, and coordinated their resolution.
→ Trained new team members on the technologies used in the project and provided guidance.

Azure Data FactorySpark SQLETL pipelines