REVATHI VIVEKANANDAN
@revathivivekanandan
Senior Azure Data Engineer specializing in scalable ETL and PySpark pipelines.
What I'm looking for
I am a Senior Azure Data Engineer with over eight years of experience designing, developing, and delivering large-scale data engineering solutions across Azure and on-premises environments. I specialize in end-to-end ETL/ELT pipelines using Azure Data Factory, Azure Databricks, Synapse Analytics, PySpark, and ADLS Gen2, and have driven measurable performance and reliability improvements for healthcare and government platforms.
I have led cloud migrations, implemented CI/CD with GitHub Actions, built serverless processing with Azure Functions, and integrated streaming solutions with Apache Kafka. My work emphasizes security and compliance (HIPAA), automation via ARM and Terraform practices, and building monitoring frameworks with Azure Monitor and Log Analytics to ensure high availability and operational excellence.
Experience
Work history, roles, and key accomplishments
Senior Azure Data Engineer
Deloitte
Sep 2023 - Present (2 years 4 months)
Designed and implemented enterprise-scale ETL/ELT pipelines on Azure Data Factory and Databricks, improving processing performance by 30–35% and reducing deployment cycles by 30% via CI/CD automation.
Data Engineer
Airtel
Oct 2014 - Nov 2017 (3 years 1 month)
Built and maintained SQL and Python ETL pipelines and Spark-based batch/near-real-time workflows for e-commerce and transactional data, improving report performance and enabling BI dashboards.
Data Engineer
Tata Consultancy Services
Oct 2011 - Sep 2014 (2 years 11 months)
Developed and automated backend reporting solutions using SQL and PL/SQL, performed performance tuning and data migration tasks to support large-scale financial reporting.
Education
Degrees, certifications, and relevant coursework
RMD Engineering College
Bachelor of Engineering, Electrical and Electronics
2007 - 2011
Bachelor of Engineering in Electrical and Electronics from RMD Engineering College completed between September 2007 and May 2011.
Tech stack
Software and tools used professionally
Splunk
Azure Synapse
Apache Spark
AWS Glue
Microsoft Azure
Amazon S3
GitHub
GitHub Actions
PySpark
AWS Data Pipeline
MySQL
PostgreSQL
Hadoop
Databricks
Terraform
Azure Resource Manager
Azure DevOps
JSON
XML
Apache Flume
Kafka
Azure Monitor
Zookeeper
Avro
Serverless
Azure Functions
SQL
Azure Blob Storage
Delta Lake
Transform
Polybase
Availability
Location
Authorized to work in
Job categories
Skills
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