NISHI JHA

Project : Panda Restaurant Group (U.S.)
Domain: Retail | Supply Chain | Commercial Analytics
Technology Stack: Azure Synapse, Azure Databricks, PySpark, ADLS, Azure Logic Apps, Python, Claude Sonnet API, Parallel Processing, Databricks AI Functions, Databricks Genie

Responsibilities & Achievements:
1)Designed and developed a scalable data engineering solution to process store-level operational and commercial data from Azure Synapse using Azure Databricks and PySpark.
2)Built parallelized data processing workflows to efficiently handle large-scale store data and improve execution performance across multiple business units.
3)Integrated Claude Sonnet AI APIs with Databricks to generate automated store-level business insights by analyzing Actuals, Plan, and Previous Year YTD performance across key KPIs including revenue growth, operational efficiency, and cost trends.
4)Developed automated pipelines to orchestrate data extraction, AI inference, validation, and structured storage of generated insights in Azure Data Lake Storage (ADLS) for downstream reporting and analytics consumption.
5)Implemented automated data quality and validation checks using Databricks AI capabilities to compare AI-generated insights with source data and ensure consistency, accuracy, and reliability.
Defined validation thresholds and quality control mechanisms to ensure only verified insights were shared with business stakeholders.
6)Built end-to-end workflow automation using Azure Logic Apps to distribute validated store insights and recommendations to business teams through automated email notifications.
7)Collaborated with cross-functional stakeholders to support data-driven decision-making through scalable analytics and AI-enabled reporting solutions.

Project: Ardagh – Unified Manufacturing Data Integration (Europe)

Domain: Packaging (Metal & Glass)

• Integrated data from 11 European plants, each contributing Parquet datasets with varied schemas.
• Assessed data structure to verify types, constraints, and relationships.
• Built ADF pipelines to ingest and validate raw data into the lakehouse with integrity checks (row counts, IDs, constraints).
• Resolved data mismatches and schema drift; applied partitioning to optimize merged dataset.
• Validated business logic and ensured accurate analytical results.

Project: Coca-Cola Hellenic Bottling Company (CCHBC)

Domain: Beverage Manufacturing

• Integrated data from SAP, SharePoint, SFTP, APIs, and SQL Server.
• Designed ADF pipelines to stage raw to golden layers in Databricks.
• Performed data quality checks, applied business rules, and handled fact/dimension modeling in Synapse.
• Delivered high-performance data pipelines supporting enterprise-wide reporting.

Project: V360 – Supply Chain Visibility

Domain: Logistics & SCM

• Developed SQL Stored Procedures and PowerApps integrations for supply chain tracking.
• Automated lane/toll/forex data processes using ADF pipelines and REST APIs.
• Delivered reliable backend solutions supporting live operational dashboards.

Project: SIRVIS – Seller & Operational Dashboard

Domain: E-commerce & Retail

• Engineered data pipelines ingesting SAP and Mirakl APIs using ADF and Databricks.
• Processed both full and incremental loads; implemented rule-based transformations.
• Served curated datasets via Azure SQL for Power BI visualizations.

• In DNB banking services, I have been working on more than 5+ routines/(Web/desktop) applications in 2 years of journey with DNB resulting in a good understanding of banking operations.
• I have also spent a year of my experience working under major banking compliance projects and has successfully delivered feasible solutions using different stack of technologies. Where compliance is top priority for banking services, I have made use of my strengths to deliver my tasks in next to neck timelines and thus helping my firm to be compliant.
• Being in agile method of working, I have also worked with my team under quality management (Testing) to ensure best of deliveries.