Vinod Kumar

Bengaluru, India
+91-9584676498 | meetvinod2@gmail.com | LinkedIn

SUMMARY

Cloud and Data-AI Expert

Senior Data Engineer with over 8 years of experience specializing in cloud and data engineering, parUcularly on Azure,
AWS, and Google Cloud PlaYorm (GCP). Proficient in designing and implemenUng robust data soluUons using Azure
services like Azure Data Factory, Azure Synapse AnalyUcs, Azure Databricks, and Azure Blob Storage, as well as AWS tools
including Redshi_, EMR, and Glue, and GCP services like Big-Query, Dataflow, and Cloud FuncUons. Experienced with
Snowflake and DBT for data warehousing and transformaUon, respecUvely. Demonstrated experUse in building high-
performance ETL pipelines, opUmizing data models, and ensuring data governance. Skilled in CI/CD tools (Jenkins), Spark
Streaming, Data Warehousing, and machine learning integraUons for real-Ume analyUcs. Strong background in Data
Vault, metadata management, and performance tuning of complex data architectures.

PROFESSIONAL EXPERIENCE
Senior Data Engineer/Architect

Insight Enterprises | June 2022 – April 2024

• Project 3:- UnitedHealth Group (Project Completed)
o Architected a cloud-based soluUon using Azure Synapse AnalyUcs and Azure Data Factory to streamline
healthcare data processing and ensure compliance with HIPAA regulaUons.
o Developed highly opUmized ETL pipelines integraUng data from various healthcare providers, enabling
real-Ume analyUcs and predicUve modeling for paUent insights.
o Leveraged Azure Databricks for big data analyUcs and machine learning operaUons, enhancing efficiency
in claims processing and medical data analysis.
o Designed data governance frameworks to ensure data security, compliance, and operaUonal scalability
within the healthcare domain.
• GeneraUve AI Training with GCP & Azure
o Led the training program focused on GeneraUve AI using both Google Cloud PlaYorm (GCP) and Azure
services for internal upskilling and project applicaUons.
o Trained and fine-tuned GeneraUve AI models on GCP's Vertex AI and Azure’s OpenAI services, creaUng
custom models for natural language processing (NLP) and image generaUon tasks.
o Developed POCs (Proof of Concepts) demonstraUng the potenUal of GeneraUve AI in automaUng
healthcare documentaUon, improving operaUonal efficiencies across healthcare providers.

Project 2: - WTW (Willis Towers Watson)

• Designed and developed scalable data architectures using Azure Synapse AnalyUcs, Azure Data Factory, and
Azure Databricks, ensuring seamless data integraUon and processing.
• Implemented ETL processes and data governance policies to ensure data integrity, security, and compliance with
industry regulaUons.
• Medallion Architecture: Leveraged the Medallion architecture for data modeling, which encompasses:
o Bronze Layer: Ingested raw data using Azure Data Lake Storage to store unprocessed data securely.
o Silver Layer: Cleaned and transformed data using Databricks and Spark to create structured datasets
ready for analyUcs.
o Gold Layer: Developed refined datasets for reporUng and analyUcs, enhancing decision-making
processes with acUonable insights.
• Integrated AI and computer vision models to automate document processing and enhance data extracUon from
images and videos, significantly improving operaUonal efficiency and accuracy in reporUng.

Personal - Individual Use

 • UUlized Azure Machine Learning for developing predicUve models that opUmized business operaUons and
idenUfied anomalies in data flows.
• Conducted performance tuning and opUmizaUon of database queries and data processing jobs, significantly
improving processing Umes and system reliability.

Project 1: - Rio Tinto

• Developed data soluUons for Rio Tinto, a global mining company, leveraging Azure cloud services to manage
large volumes of structured and unstructured data.
• UUlized Azure Blob Storage to store unstructured data such as images, videos, and sensor data generated from
mining equipment, ensuring cost-effecUve storage soluUons.
• Used Azure Data Lake Storage for scalable management of structured and unstructured data, facilitaUng efficient
data access and analysis.
• Integrated data from various sources, including on-premises and cloud-based, into centralized repositories using
Azure Data Factory.
• UUlized Azure Databricks for real-Ume data processing and machine learning model execuUon to generate
insights from mining data for operaUonal opUmizaUon.
• Implemented Kubernetes to manage containerized applicaUons running in the Azure cloud, allowing for
automated scaling and management of data processing workloads.
• Used DBT (data build tool) for transforming data in the warehouse, enabling analysts to perform analyUcs on
transformed data efficiently and improving collaboraUon among data teams.
• Performed performance tuning of SQL soluUons to meet Rio Tinto’s expectaUons, and handled all database
administraUon tasks using Managed Instance, ensuring high availability and performance.
• Experience with Azure Data Factory, Azure Databricks, Data Vault, and Azure SQL Database for building scalable
pipelines and managing data processing workloads.
• Implemented scaling strategies using Managed Instance to automaUcally adjust resources based on changing
workloads, ensuring opUmal performance and cost efficiency.

Senior So_ware Engineer

Publicis Sapient | June 2021 – June 2022

Project 1: Sephora (MigraUon Project)
• Led the migraUon of data from Oracle databases and various CRM tools to Azure, ensuring minimal downUme
and data integrity.
• UUlized Azure Data Factory for orchestraUng data movement and transformaUon, enabling seamless migraUon
workflows from on-premises Oracle systems to Azure SQL Database.
• Implemented Azure Logic Apps for integraUng CRM data with other business applicaUons, enhancing data
accessibility and usability across departments.
• Conducted data cleansing and transformaUon using Azure Databricks, leveraging Spark for processing large
volumes of data efficiently.
• Developed detailed migraUon strategies and documentaUon to ensure compliance with business requirements
and regulatory standards.
• Established monitoring and error-handling processes to track data migraUon progress and resolve issues in real-
Ume.

Data Engineer

GlobalLogic | July 2016 – May 2021

Project 1: The Estée Lauder Companies
• Designed and implemented a highly available data warehouse soluUon using AWS S3, AWS Lambda, AWS EMR,
and Athena for large-scale data processing.
• Developed ETL pipelines using AWS Glue to extract data from various sources, transform it, and load it into
Redshi_ for analyUcal processing.

Personal - Individual Use

 • Created data models and opUmized database queries using AWS Redshi_ to handle high volumes of retail data
and generate business insights.
• Set up AWS CloudFormaUon for infrastructure automaUon and AWS CloudFront for faster data distribuUon
across regions.
• Monitored and opUmized real-Ume data ingesUon using AWS Kinesis, reducing latency and improving reporUng
accuracy.

Project 2: Dentsply Sirona

• Migrated on-premises data to Azure SQL Database and built a scalable Azure Synapse AnalyUcs environment for
business reporUng and analyUcs.
• Developed data pipelines using Azure Data Factory for seamless integraUon between mulUple data sources and
Azure Data Lake for cost-effecUve, secure data storage.
• Implemented real-Ume data processing with Azure Stream AnalyUcs and Azure Event Hubs to support criUcal
business operaUons.
• Used Azure Databricks to process large datasets, enabling predicUve analyUcs and machine learning workflows
for opUmizing producUon processes.
• Focused on data governance, applying Azure’s Data Catalog for data discovery and Azure Key Vault for securing
sensiUve informaUon.
• Deployed and monitored Azure Logic Apps and Azure FuncUons to automate key business processes and
integrate with third-party applicaUons.
Project 3: American Airlines (GCP Services & MongoDB)
• Enhanced data soluUons for American Airlines using Google Cloud PlaYorm (GCP) services to manage large-scale
airline operaUons data, improving data efficiency and decision-making processes.
• Developed and opUmized ETL pipelines using Google Cloud Dataflow to process streaming data from flight
operaUons and customer service systems, ensuring real-Ume analyUcs.
• Leveraged Google Big-Query for analyUcal data storage, providing scalable and cost-efficient querying for flight
scheduling, passenger data, and operaUons insights.
• Integrated MongoDB with Google Cloud FuncUons to provide real-Ume data syncing and support event-driven
architectures across airline operaUonal systems.
• Implemented Google Cloud Pub/Sub for handling real-Ume messaging and communicaUon between flight
operaUons systems, enabling immediate responses to operaUonal events.
• Built and deployed machine learning models using Google Vertex AI to predict delays and opUmize resource
allocaUon across airports, enhancing the efficiency of operaUons.
• Ensured data security and governance using Google Cloud IAM and Google Cloud Storage and implemented data
protecUon protocols with Cloud KMS.

EDUCATION

• Master of Science (M.S.) in Computer Science

Liverpool John Moores University | Expected CompleUon: Nov 2023

• Bachelor of Technology (B.Tech.) in Computer Science

ITM University, Gwalior | 2012 – 2016

Licenses & CerUficaUons

DP-200 ImplemenUng an Azure Data SoluUon - Microso_ a6ee6971-71ce-4cc9-9420-81e90u55eb6

Microso_ CerUfied: Azure AI Engineer Associate - Microso_ a7d6f170-1f55-41d2-8686-cb9ccc30add9

AZ-400 Designing and ImplemenUng Microso_ DevOps SoluUons - Microso_ 15263153-a6fa-4eff-8400-

6891eb24baf5

Personal - Individual Use

 AZ-303 Microso_ Azure Architect Technologies - Microso_ 47246264-924d-4529-bfa4-e7868b568716

Microso_ AZ-500: Microso_ Azure Security Technologies/Microso_ CerUfied: Azure

Security Engineer Associate - Microso_ 8fc26d52-6e49-467a-acf8-289226a138
Microso_ CerUfied: Azure Administrator Associate (AZ-104: Microso_ Azure Administrator) -
Microso_ Issued Jul 2021 - Expires Jul 2022 30749c47-0279-4ac7-b03e1be40ae7771.

AZ-104: Microso_ Azure Administrator (Microso_ CerUfied: Azure Administrator Associate) -

Microso_30749c47-0279-4ac7-b03e-1be40ae7771f

DP-900: Microso_ CerUfied: Azure Data Fundamentals/Database Administrator, Data

Analyst, Data Engineer, Developer - Microso_ 44f024ad-65af-4785-bc74-91cd2e8f1476

Microso_ CerUfied AZ-304: Azure SoluUons Architect Expert/Microso_ Azure Architect

Design - Microso_ Issued Jul 2021 - Expires Jul 2022 6538eb5f-8e5a-4da6-8c6ac07a5d197584.

AZ-304 Microso_ Azure Architect Design/ Microso_ CerUfied: Azure SoluUons Architect
Expert - Microso_ 2997b71e-56b3-49d1-bub-2c9f7fe06b9a

DP-100: Designing and ImplemenUng a Data Science SoluUon on Azure- Microso_

CerUfied: Azure Data ScienUst Associate - Microso_ 3599eff3-004a-401e-85d4-900b25bca8u

DP-203: Data Engineering on Microso_ Azure-Microso_ CerUfied: Azure Data Engineer

Associate - Microso_ Issued Nov 2021 - Expires Nov 2022
Microso_ CerUfied: -AZ-305: Designing Microso_ Azure Infrastructure SoluUons- Azure
SoluUons Architect Expert - Microso_ 4240ab1e-7a50-4295-821c-18ea837f59aa
AZ-305: Designing Microso_ Azure Infrastructure SoluUons - Microso_ 5ea2c941-232e-4a8d-8717-0eb421d0ddf3

Microso_ CerUfied: Azure Data ScienUst Associate - Microso_ Issued May 2023 - Expires May 2024
0a3caa9c-d25c-453b-bf7b-926c265b5016.

TECHNICAL SKILLS
• Cloud PlaYorms: Azure (Data Factory, Synapse AnalyUcs, Databricks, Blob Storage, Cosmos DB), AWS (S3, Glue,
Redshi_, EMR, Lambda), GCP (BigQuery, Dataflow, Vertex AI, Pub/Sub, Cloud FuncUons)
• Big Data & ETL: Spark, Hadoop, Kawa, Flink, Data Vault
• Data Warehousing: Azure Synapse, Snowflake, Redshi_, BigQuery, PostgreSQL
• CI/CD Tools: Jenkins, GitHub AcUons, Terraform, Docker, Kubernetes
• Programming Languages: Python, Java, SQL, C#, Bash
• Databases: Azure SQL, Cosmos DB, MongoDB, PostgreSQL.
• Data Modeling: Dimensional Modeling, Data Lakes, Data Mesh, Data Quality, Governance
• Machine Learning: Azure Machine Learning, Vertex AI (GCP), OpenAI (Azure), MLOps
• Data Governance: Data Quality, Lineage, Data Catalog, Data Mesh, Vault, APIs

Personal - Individual Use