Venkata Venna

• Designed, built, and deployed scalable data pipelines to support regulatory and enterprise analytics workloads, translating federal business requirements into production-ready data engineering solutions.
• Implemented end-to-end ETL and ELT workflows using Ab Initio, and PySpark, ensuring high performance, data integrity, and reliable batch processing at scale.
• Developed and maintained logical and physical data models for CCAR datasets, performing metadata scans, PG classification, and CCMS registration in alignment with enterprise data governance standards.
• Engineered data governance controls by validating data dictionary entries, enforcing classification policies, and reducing redundant data across databases, data lakes, and staging environments.
• Modernized legacy reporting pipelines by converting PL/SQL-based processes to distributed Spark jobs and building Tableau dashboards to automate CCAR reporting and analytics delivery.
• Built cloud-native ingestion pipelines using REST/PUT APIs with publisher–subscriber patterns, Control-M scheduling, and automated dynamic data loads for persistent datasets using Spark and Java.
• Designed and executed AWS-based data lake ingestion and extraction POCs, moving data from S3 into Exadata using Terraform-driven infrastructure provisioning and IaC best practices.
• Developed event-driven serverless workflows using AWS Lambda (Python), integrating with S3, Glue Crawlers, and Athena to enable scalable, on-demand ETL processing.
• Delivered high-performance analytics and reporting solutions on AWS using Apache Spark, focusing on scalability, reliability, and cost efficiency for large datasets.
• Drove cloud optimization and engineering best practices by performing cost-benefit analysis (CBA), recommending efficiency improvements across AWS, VSI, and GKP, maintaining ≥75% code coverage through automated APPFIT scans.
• Created Snowflake tables aligned with enterprise data governance, security classifications, and data modeling standards.
• Implemented Snowflake table structures to support structured and semi-structured data ingestion from cloud data lakes.
• Collaborated with cross-functional teams to implement solutions aligned with business objectives.

Skill Set: Oracle, PL/SQL, Python, Java, PySpark, AWS Lambda, S3, EC2, EKS, ELB, EMR, Glue, Athena, Airflow, Terraform, Snowflake, Control-M, Erwin, API, Tableau, GitHub, Maven, Jules, VS Code, Jupyter Notebook, IntelliJ, Kafka, Grafana, Ab initio, Cassandra – CQL, GenAI / LLM

The Vanguard Group - Malvern, PA May 2012 - May 2018

• Initiated service request architecture to improve the business workflow for applications: Closely working with Data Architects in designing the new applications and performance improvements. Providing ad hoc reports according to business users.
• Coordinating with product owners to ensure product compliance with new and ongoing changes in functional requirements.
• Participated in sprint planning and sprint retrospections.
• Compliance with security standards and SLAs. Working with DTS to process the data between Vanguard and and third-party vendors. Participating in architectural design meetings to understand and design the applications.
• Provided presentations to the team on Big Data. Participated in Cassandra POC. Identified the relational Data bases to be converted to Big Data store.
• Designed and developed interactive Power BI dashboards and reports to deliver actionable business insights.
• Integrated data from data warehouses, data lakes, and relational databases, ensuring data accuracy and performance.
• Mentored junior engineers, fostering skill development and knowledge sharing within the team.
• Led development of scalable software solutions, enhancing application performance and user experience.

State Farm Insurance, Bloomington, IL Sep 2008 - Dec 2009

Auto Owners Insurance, Lancing, MI Jan 2010 - May 2012

Progressive Insurance, Cleveland, OH

Regence Health Care (BCBS) - Seattle, WA Dec 2003 - Oct 2005