KAVYA CHOWDARY
Dallas,
Summary
Results-oriented professional with robust background in Product Management and Agile frameworks. Known for fostering team collaboration and driving projects to successful completion. Reliable in adapting to evolving requirements and prioritizing key deliverables, showcasing strong ability to manage stakeholder expectations.
Overview
12
12
years of professional experience
Work History
Technical Product Owner
CVS Health
Dallas, TX
07.2022 - Current
- Product Ownership & Strategy: Defined and executed the product vision and roadmap for enterprise data modernization initiatives, aligning technical solutions with business objectives and ensuring measurable outcomes across analytics and reporting functions.
- Cloud Migration Leadership: Spearheaded the migration from on-prem Hadoop infrastructure to Google Cloud Platform (GCP), leveraging native services such as BigQuery, Dataflow, and Pub/Sub to increase scalability by 30% and reduce infrastructure costs.
- Data Pipeline Transformation: Partnered with engineering teams to re-architect ETL pipelines using Apache Beam and Dataflow, improving data processing performance by 40% and enabling near real-time analytics capabilities.
- Stakeholder Collaboration: Served as the liaison between technical and business teams—including underwriting, claims, and risk management—to gather requirements, refine user stories, and prioritize features that drive business value.
- Agile Delivery: Led Agile ceremonies such as sprint planning, backlog refinement, and sprint reviews; ensured cross-functional alignment and timely delivery of product increments according to roadmap priorities.
- Risk & Compliance Oversight: Ensured all cloud-based data products complied with security, privacy, and industry regulations, mitigating potential compliance risks during platform transition.
- Business Intelligence & Insights: Partnered with BI teams to enhance reporting in Tableau, enabling faster, more accurate insights for executives and business leaders.
- Performance Optimization: Collaborated with data engineering teams to tune BigQuery and Dataflow performance, improving cost efficiency and reducing operational expenses by 25%.
- Training & Enablement: Delivered training sessions for cross-functional teams to drive adoption of new cloud data platforms and analytics tools such as Google Data Studio.
- Issue Management & Continuous Improvement: Managed and resolved migration-related challenges, including pipeline errors and data transfer bottlenecks; implemented monitoring and feedback loops that improved development cycle time by 15%.
Product Owner - Tech Lead
Nationwide Insurance
Dallas, TX
02.2019 - 06.2022
- Feature Story Delivery & Optimization: Led end-to-end Data Product delivery of an enterprise-wide data transformation platform - Feature Store, integrating AWS, Databricks, and Snowflake to optimize data pipelines, resulting in a 30% reduction in data processing times and improving operational reporting efficiency.
- Cross-Functional Collaboration: Directed collaboration between Data Engineering, Data Science, Business Intelligence, and Compliance teams to ensure alignment between data product strategy, enterprise goals, and regulatory compliance. This resulted in significant improvements in both analytics capability and reporting clarity for senior leadership.
- Data Governance Framework: Architected and implemented a comprehensive Data Governance Framework, introducing robust processes for data quality monitoring, lineage tracking, and data classification, which enhanced the trust and compliance posture of the organization's data assets.
- Modernized Data Pipelines: Overhauled global data pipelines using AWS Services(S3, Glue, Airflow), and Databricks, enhancing data availability, scalability, and reducing operational overhead. Enabled the seamless integration of multiple internal and external data sources for better real-time insights.
- Unified Analytics Layers: Led the unification of disparate data layers in Power BI and Tableau, improving data consistency, eliminating redundant KPIs, and increasing the clarity of executive reporting, enabling data-driven decision-making across business units.
- Product Roadmap Execution: Designed and delivered multi-quarter product roadmaps, aligning with strategic business priorities and ensuring timely delivery of high-value features. Established clear milestones, driving stakeholder alignment and fostering transparent communication with key business leaders.
- Agile Leadership & Mentorship: Guided cross-functional teams in adopting Agile best practices, facilitating sprint planning, backlog refinement, and executive demos via tools like Jira and Confluence. This resulted in a 25% increase in delivery efficiency and continuous improvement in team performance.
- Enterprise Enablement & Data Literacy: Led enterprise-wide enablement sessions focused on data product usage, data governance policies, and self-service analytics, increasing data literacy and encouraging the broader organization to embrace data-driven decision-making.
- Business Requirement Translation: Actively translated business requirements into epics and user stories, ensuring clear alignment with stakeholder objectives and technical feasibility, and effectively communicating the product vision to both technical and non-technical stakeholders.
- Backlog Prioritization & Sprint Planning: Conducted regular backlog grooming sessions, effectively balancing stakeholder priorities with technical feasibility, ensuring that the team focused on the highest-impact tasks that aligned with business goals.
- Acceptance Criteria Definition: Defined and validated acceptance criteria for epics and user stories, ensuring that all features met business needs, regulatory requirements, and technical standards before release, resulting in high-quality product outputs.
- Sprint Demos & Testing: Actively participated in sprint demos and conducted thorough testing of deliverables, reviewing them against defined acceptance criteria to ensure that all features and functionalities met stakeholder expectations and compliance standards.
Lead Data Engineer
Beam Suntory
Chicago, IL
10.2016 - 02.2019
- Full SDLC Participation: Led the development lifecycle, including requirement gathering, design, implementation, testing, deployment, and code reviews to ensure high-quality, scalable solutions for retail data processing and analytics.
- Migration to Cloudera Data Platform (CDP): Contributed to the migration of on-premise Hadoop workloads to Cloudera Data Platform (CDP), optimizing system performance and scalability, and ensuring smoother data processing pipelines for retail operations.
- Data Ingestion Frameworks: Built Python/PySpark-based ingestion frameworks to extract and load structured data from relational databases (IBM DB2, SQL Server, Oracle, Cache) into the Hadoop Data Lake, improving the speed and efficiency of data integration.
- Data Parsing & Transformation: Designed PySpark components to parse and ingest fixed-width, nested XML, and JSON files into the Hadoop ecosystem, enabling structured data storage and transforming complex data formats into queryable datasets.
- Complex Data Transformation: Developed complex PySpark queries for data transformation, including dynamic schema modifications, optimized selective reads on Hive, and joins to streamline data processing for downstream analytics and reporting.
- XML Parsing with Spark: Utilized Scala Spark API and XPath for efficient parsing of XML data into Hive tables, optimizing performance and reducing data processing times. Converted complex HQL queries into Spark equivalents using Spark-SQL and PySpark.
- Spark Applications for Data Workflows: Developed Spark applications for data validation, cleansing, transformation, and aggregation, supporting retail-specific business use cases such as sales trends, inventory management, and customer analytics.
- Automated Data Ingestion: Automated the ingestion of structured and semi-structured data from various sources using Zena Scheduler and Apache NiFi, improving efficiency and ensuring continuous data flow into the Hadoop ecosystem.
- Data Optimization: Addressed complex business needs by building and optimizing Spark DataFrames over Hive tables, ensuring high performance and low-latency queries for real-time analytics.
- Incremental Data Loads: Implemented incremental and differential data loads using SSIS, ensuring that retail data pipelines remained up-to-date with minimal processing overhead and were scheduled for daily execution.
- System Integration & Support: Led system integration testing, UAT, and production deployment processes, providing ongoing post-production support to ensure seamless functionality and user satisfaction.
- Troubleshooting & Optimization: Demonstrated strong troubleshooting abilities by identifying and resolving runtime issues in the Hadoop ecosystem. Continuously optimized data workflows to ensure smooth processing of large-scale retail data.
- Cloud & Big Data Expertise: Gained hands-on experience across Cloudera Data Platform, Azure Cloud, and AWS, with a solid understanding of object storage and big data performance tuning, ensuring the platform's reliability and scalability.
Big Data Engineer
Eli Lilly
Indianapolis, IN
03.2014 - 09.2016
- Designed Scalable Pipelines: Built large-scale distributed data pipelines using the Hadoop ecosystem to process multi-terabyte datasets efficiently.
- Optimized HBase Performance: Created and loaded HFiles into HBase for fast, low-latency access to customer data without performance degradation.
- PII Data Management: Developed HBase schemas to securely store diverse formats of PII data across business portfolios.
- Kafka Integration: Implemented Apache Kafka for real-time data ingestion and processing, enabling fault-tolerant publish-subscribe communication.
- Stream Reliability: Built robust Kafka producers and consumers to ensure consistent, high-throughput data delivery.
- Workflow Automation: Automated end-to-end data pipelines and ensured cluster synchronization using custom shell and Python scripts.
- Job Scheduling: Utilized Zena Scheduler to manage MapReduce workflows, reducing manual effort and ensuring timely execution.
- Service Coordination: Employed Zookeeper for cluster coordination, leader election, and configuration management.
- Hive Development: Created Hive tables, loaded structured data, and wrote HiveQL queries to trigger backend MapReduce jobs.
- Cassandra Export: Exported large datasets into Cassandra with well-designed column families for efficient query performance.
- System Documentation: Authored comprehensive technical documentation covering system workflows, architecture, and operational procedures.
- Agile Development: Actively participated in Agile ceremonies including daily stand-ups, sprint planning, and retrospectives to support iterative development.
Education
Master of Science -
Purdue University
Indianapolis, IN05-2018
Bachelor of Science -
Gitam University
Hyderabad, India03-2014
Skills
- Data-driven business analysis & decision making
- Product lifecycle management
- Roadmap development
- Agile & Scrum methodology
- Stakeholder relationship management
- Risk management
Timeline
Technical Product Owner
CVS Health
07.2022 - Current
Product Owner - Tech Lead
Nationwide Insurance
02.2019 - 06.2022
Lead Data Engineer
Beam Suntory
10.2016 - 02.2019
Big Data Engineer
Eli Lilly
03.2014 - 09.2016
Master of Science -
Purdue University
Bachelor of Science -
Gitam University