Jul 2024 – Jun 2025 · 11 mos · Sunnyvale, CA · On-site

• Locations: Austin, TX Gigafactory and Palo Alto, CA HQ
• Worked on factory manufacturing data for CyberTruck and Model SXY3 production related to throughput, production control, and quality across all Gigafactories(Fremont, Reno, Austin, Buffalo).
• Creating Airflow DAG's for loading Supply Chain, Operations, Packaging, Inventory data from WMS systems to Vertica/Clickhouse databases and created denormalized table structures.
• Implemented Kafka Jet streams to load data into Clickhouse tables and writing the data with idempotent results using Debezium MySQL connector for SCD-2 type implementation.
• Created KPI's like Utilization Ratio, Aging lines Inventory, Stagnant Inventory numbers, In/Out Network parts for Tesla's Service teams located at 16 RDC's across US.
• Developed Teams Relay Bots using Graph API's and Python for notifications system for reducing the manual hours by 40% hosted on Azure using Bot Framework.
• Revamped complex SQL queries for customized view creation and consolidated tableau dashboards with 40% load-time optimization.
• Created a incremental pipeline pulling data from Splunk Data logs via REST API calls for Live metrics and log monitoring.

May 2024 – Aug 2024 · 3 mos · Memphis, Tennessee, United States · On-site

• Constructed Data workflows to migrate data from WMS-Oracle Systems onto Azure Tables using Databricks Notebooks in the SML Team.
• Automate existing Python scripts to deliver webmail service using Logic Apps/Power Automate, with 33% in operational efficiency.
• Developed ADF pipelines, Databricks Notebooks, and Flask API calls for 3rd party application integration like SMTP, Microsoft 365 suite.
• Used Web Scraping using Python scripts to extract attendance data and used Azure DevOps for Source Versioning and CI/CD releases.

Jan 2024 – May 2024 · 4 mos · Richardson, Texas, United States

• Working as a Teaching Assistant for Spring 2024 under Professor Sheen Levine, PhD, Visiting Associate Professor, Organizations, Strategy and International Management for Courses like AI & Entrepreneurship, Making Choices in Free Market Systems and Business Data Warehousing

Sep 2023 – Dec 2023 · 3 mos · Richardson, Texas, United States

• Scanning archival materials, processing archival collections, creating inventory listings, shelving.
• Shifting archival holdings including applying barcodes on containers, and recording locations coordinates and container profiles.
• Data digitalization of archival content management ArchivesSpace (AS) as well as in library’s cataloging system ALMA.
• Developing and refactoring of python codes to convert XML format to TARO compatible format.

May 2022 – Jun 2023 · 1 yr 1 mo · Bengaluru, Karnataka, India

• Empower Walmart and our value chain partners to accelerate Sustainability goals in Climate, Waste, Nature, and People.
• NextGen Gigaton enables Walmart to Discover, Assess, Manage and Report Sustainability initiatives in achieving Zero Emission by 2040, 1 Gigaton GHG emission avoidance across value chain by 2030, and sourcing of 100% renewable energy by 2035.
• Part of the Global Governance Global Responsibility(GGGR) team which comes under the umbrella of EBS ( Enterprise Business Services)
• Part of the team responsible for modernizing of 55+ complex Alteryx, 24 + workflows in DataStage (sunsetting tools) workflows in Spark/Scala on GCP which reduced the licensing costs ($3000 per user).
• Working with business to optimise and create BQ views for business dashboard consumption for IROCC initiative.
• Tools Used: Azure SQL DB,BigQuery, GCS,Scala, Apache Spark, Maven, Hive, Airflow DAG's, Alteryx, MongoDB, Pandas, REST API.

Apr 2021 – Apr 2022 · 1 yr · Bengaluru, Karnataka, India

• Worked with a top CPG/FMCG giant in their Supply Chain Analytics team for Growth Momentum Project.
• Growth Momentum involved identifying key SKU's across each markets and also consume Sales, Market and Ifinance data for demand forecasting and also identify whitespaces based on Market attractiveness and company potential.
• Worked in a team as a Data Engineer implementing ML based framework which provide users prescriptive insights/recommendations from their historical data, which increased their forecasts by 27%.
• Worked with Azure, ADF, Databricks, Synapse Analytics, Logic Apps, ADLS Gen 2, Event hubs, Streaming Analytics, Azure Devops and Anaplan etc.
• Experience in working with Big Data technologies like Hadoop, Distributed Systems, Hive, HBase, Apache Spark, Azure DevOps etc
• Involved in user requirement gathering, Architecture Draft and LLD Design creation for InfoSec requirements.
• Involved in Wireframing , planning and cross functional meetings with Stakeholders.

May 2019 – Mar 2021 · 1 yr 10 mos · Bengaluru, Karnataka, India · On-site

• Top UK Insurance Firm
• =========================
• 1) Worked for in a Finance ambition(FuB) project for a top British insurance client and their parent group.
• 2) Worked in implementing Data Migration, Cloud Datawarehousing, and conforming data to latest IFRS17 standards.
• 3) Experience in understanding data and statistics from heterogeneous sources and creation of Target-to-Source Mapping document.
• 4) Raw Data passed Data validation, profiling and Curation checks.
• 5) Worked in orchestrating Data pipelines using ADF, populating control tables, Dimension and Fact table loading for huge volumes of data using Azure Synapse Analytics (Azure DWH)
• 6) Reconciliation metrics to cross validate the results with reference data store. (Validation of the suspense logic)
• 6) Data Modelling (Tabular) using Azure Analysis Services/Power BI
• 7) Creation of BI reports to be consumed by Business/Product team for better operations.
• 8) Databricks, HdInsight Cluster used for specific business scenarios for optimization of pipeline runs.
• Fortune #1 Company:
• =============================
• 1) Worked with Fortune #1 client in their connected products business vertical and leveraged their Cloud-IOT architecture to implement Demand Shedding and Event Management tasks.
• 2) Demand Shedding involved efficient power savings and cost reductions at client stores in US during non-peak hours through Azure IOT instances and Event management involved the scalability of resources during high peak hours.
• 3) Reports created based on the analysis of these events and shared across teams based on the ownership
• 4) Alert rule creation for the Azure instances for Throttling , %CPU, %SU, Pods failed etc.
• 5) Execution of Python/SQL notebooks on ADLS gen 2 storage for cold data retrieval process.(Databricks)
• 6) Exposure to IOT components like IOT hub, Event Hub, Cosmos DB, ASA, Logic Apps, Azure Functions, AKS, PowerShell etc.