Vardhan Seepala

Lead Data Engineer | All Things Data

👋 Hi, I'm Vardhan Seepala

🚀 Lead Data Engineer with 6+ years of experience architecting enterprise-scale data solutions across cloud platforms. Expert in designing scalable data pipelines, implementing modern data architectures (Data Vault 2.0, Medallion, Lambda/Kappa), and optimizing OLAP/OLTP systems that drive business intelligence for Fortune 500 companies.


Data Engineering Specializations ✨

  • Cloud Data Platforms: AWS, GCP, Azure - Multi-cloud data lake and warehouse architectures
  • Data Modeling: Star/Snowflake schema, Data Vault 2.0, Medallion Architecture (Bronze-Silver-Gold)
  • Real-time Processing: Stream processing with Apache Kafka, Dataflow, and event-driven architectures
  • Modern Data Stack: dbt, Airflow, Terraform, Kubernetes for DataOps and infrastructure automation
  • Performance Optimization: Query optimization, data partitioning, and cost reduction strategies

Data Architecture & Methodologies 🏗️

Data Vault 2.0

Implemented enterprise data warehouses using Data Vault 2.0 methodology, enabling agile data modeling and maintaining data lineage for complex business domains.

Medallion Architecture

Designed Bronze-Silver-Gold data lake architectures for progressive data refinement, ensuring data quality and enabling self-service analytics.

Lambda & Kappa Architectures

Built real-time and batch processing systems using Lambda/Kappa architectures for handling high-velocity, high-volume data streams.

OLAP & OLTP Optimization

Optimized transactional systems (OLTP) and analytical workloads (OLAP) for maximum performance and cost efficiency.

Experience Snapshot 💼

Lead Data Engineer @ Viral Nation (Jun 2023 – Present)

  • Architected CDC pipelines (Cloud SQL → BigQuery) using GCP Datastream, implementing Medallion Architecture for progressive data refinement
  • Deployed Terraform IaC for Datastream on private VPC, implementing DataOps best practices and reducing manual setup by 50%
  • Engineered dbt models using dimensional modeling (Star Schema) unifying 10+ data sources, reducing data errors by 80%
  • Built Apache Beam streaming pipelines for real-time data processing, enabling sub-second decision-making for marketing campaigns
  • Implemented CI/CD for ML models on Azure ML Studio with Kubernetes scaling, reducing deployment time by 35%
  • Designed PySpark ETL pipelines in Azure Synapse with optimized data partitioning for campaign performance analytics

Data Engineer Co-Op @ BDO (Jan 2023 – Apr 2023)

  • Redesigned Azure Data Factory pipelines using dependency-based orchestration, reducing processing time by 30%
  • Developed Power BI dashboards with real-time MQTT data integration for manufacturing IoT analytics
  • Automated KQL query generation for Azure Data Explorer, accelerating data extraction by 25%

Senior Software Engineer @ Oracle Cerner (Aug 2019 – Dec 2021)

  • Designed AWS EMR clusters with optimized instance types and spot instances, reducing processing costs by 30%
  • Implemented CloudFormation templates for AWS IAM role automation, achieving 90% error reduction
  • Built healthcare data normalization pipelines following HL7 FHIR standards for 10K+ patient records daily
  • Developed automated testing frameworks reducing integration testing time by 70%

DevOps Engineering Intern @ Sigmoid Pvt Ltd (Apr 2019 – Jul 2019)

  • Created Datadog monitoring dashboards for cluster health, reducing downtime by 50%
  • Delivered POCs for AWS cost optimization, achieving 20% cost reduction and 15% client acquisition increase

Technical Expertise 🛠️

Cloud Platforms

  • AWS: EMR, Redshift, S3, Lambda, CloudFormation
  • GCP: BigQuery, Dataflow, Datastream, Pub/Sub
  • Azure: Synapse, Data Factory, ML Studio, Data Explorer

Programming & Frameworks

  • Python: Pandas, Apache Beam, PySpark, PyTorch
  • SQL: PostgreSQL, BigQuery, Snowflake, T-SQL
  • Java: Spring Boot, Microservices, Kafka Streams

Data Engineering Tools

  • Orchestration: Apache Airflow, Prefect
  • Transformation: dbt, Spark, Hadoop
  • Streaming: Apache Kafka, Apache Beam

Data Modeling & Architecture

  • Dimensional Modeling: Star/Snowflake Schema
  • Data Vault 2.0: Hubs, Links, Satellites
  • Medallion Architecture: Bronze-Silver-Gold

DevOps & Infrastructure

  • IaC: Terraform, CloudFormation, ARM Templates
  • Containers: Docker, Kubernetes, Helm
  • CI/CD: Jenkins, GitHub Actions, Azure DevOps

Analytics & Visualization

  • Business Intelligence: Looker, Power BI, Tableau
  • Data Science: Jupyter, MLflow, Apache Superset
  • Monitoring: Datadog, Grafana, Prometheus

Certifications & Continuous Learning 🏆

AWS Certified Solutions Architect

Expert in designing scalable, fault-tolerant systems on AWS

Google Cloud Professional Data Engineer

Specialized in GCP data engineering and machine learning

Azure Data Engineer Associate

Certified in Azure data platform services and architecture

Databricks Certified Data Engineer

Expert in Apache Spark and lakehouse architecture

Education 🎓

  • Master of Applied Computing – University of Windsor, Canada
  • Bachelor of Engineering in Computer Science – Sir MVIT, India

Featured Data Engineering Projects 💻

Latest Technical Articles 📝

Let's Build Something Amazing Together 🚀

Ready to transform your data infrastructure? I specialize in building scalable, cost-effective data solutions that drive business value.