Purushotham User
@purushothamuser1
Senior Data Engineer specializing in Azure ETL/ELT, streaming pipelines, governance, and cost-optimized analytics.
What I'm looking for
I’m a Senior Data Engineer with 7+ years of experience designing and maintaining ETL/ELT pipelines, data ingestion, integration, data modeling, and enterprise data warehousing on the Azure platform.
I build large-scale workflows with Azure Data Factory, Synapse Analytics, Microsoft Fabric, Data Lake, and Databricks—delivering reliable ingestion, migration, and analytics at scale. I also develop real-time streaming solutions with Azure Event Hubs, Kafka, and Spark Streaming, using Change Data Capture to keep latency low.
On the transformation and modeling side, I use SQL, Python, PySpark, and DBT (with Spark SQL, Pandas, NumPy, and SciPy) to prepare datasets for reporting, analytics, and machine learning. I design and optimize warehouses in Snowflake and Azure Synapse Analytics using partitioning, clustering, and indexing to improve query performance and scalability.
I’m equally focused on governance and production excellence: I apply Azure Active Directory, RBAC, Key Vault encryption, and compliance practices for HIPAA, GDPR, and PCI-DSS. In my recent role at Med-Metrix, I improved data availability by 35%, achieved 40% faster delivery with 25% lower computing expenses, and reduced job failures by 30% by optimizing pipelines, Spark jobs, and Airflow DAGs. I also automate orchestration and CI/CD with Airflow, NiFi, Azure DevOps, Terraform, Docker, and Kubernetes—and I mentor teammates through code reviews and knowledge sharing.
Experience
Work history, roles, and key accomplishments
Senior Data Engineer
Med-Metrix
Aug 2023 - Present (2 years 7 months)
Designed real-time and batch data integration pipelines across Azure (Cosmos DB, Data Lake, Data Factory, Synapse, Fabric, Event Hubs) to deliver healthcare data for downstream analytics. Improved data availability by 35%, accelerated delivery by 40% while reducing computing costs by 25%, and decreased production job failures by 30% through Spark optimization and pipeline tuning.
Migrated on-premise SQL workloads to Azure Data Lake and Azure SQL, building secure batch and streaming ETL pipelines for risk analytics and regulatory reporting. Reduced reporting query time by 30% with star/snowflake schema modeling, automated 40+ Airflow DAGs to achieve a 99.9% success rate, and implemented CDC-based Kafka/Spark streaming for real-time financial fraud and AML monitoring.
Education
Degrees, certifications, and relevant coursework
St. Thomas University
Master of Science, Computer and Information Systems
Earned a Master of Science in Computer and Information Systems at St. Thomas University.
Tech stack
Software and tools used professionally
Fivetran
Matillion
Azure HDInsight
Azure Synapse
Apache Spark
Talend
SAS
DOMO
GitHub
GitLab
Kubernetes
Azure Kubernetes Service
Jenkins
NumPy
Pandas
PySpark
dbt
DB
Sqoop
PostgreSQL
MongoDB
Cassandra
Hadoop
HBase
Gmail
Databricks
Figma
Terraform
Azure Resource Manager
Azure DevOps
Jira
Java
JSON
PowerShell
Apache Flume
scikit-learn
Kafka
RabbitMQ
Apache NiFi
Azure Monitor
Linux
Azure Active Directory
Azure Functions
Azure SQL Database
Airflow
SQL
Azure Cosmos DB
Azure Blob Storage
SciPy
Refine
Delta Lake
Azure Logic Apps
Cosmos
Bash
Transform
Microsoft Fabric
Dynamic
Task
Factory
Unify
Availability
Location
Authorized to work in
Job categories
Skills
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