Sri Viharika Nunna

• Results-driven Senior Data Engineer with 12+ years of progressive experience designing, building, and optimizing enterprise-scale data pipelines, real-time streaming architectures, and data warehousing solutions across highly regulated industries including retail, banking, healthcare, defense, and financial services. • Proven track record of delivering scalable ETL/ELT workflows, lakehouse architectures, and analytics-ready data platforms that drive measurable business outcomes — from reducing fraud false positives by 38% to improving query performance by up to 60% and cutting pipeline maintenance effort by 40%. • Deep expertise in Apache Spark, PySpark, Apache Kafka, Apache Airflow, Snowflake, Delta Lake, and Apache Iceberg, with strong command of Python, SQL, and Java for building robust data engineering solutions across batch and real-time processing paradigms. • Hands-on experience integrating heterogeneous data sources — including Oracle ERP, SAP, Salesforce, EHR systems, and third-party APIs — into unified analytical data lakes and warehouses supporting downstream BI, ML, and GenAI consumption patterns. • Skilled in implementing data quality frameworks (Great Expectations, Deequ), data governance and access control policies, and compliance-aligned pipeline architectures adhering to HIPAA, PCI-DSS, and SOC 2 standards. • Experienced in deploying and managing data infrastructure as code using Terraform, Docker, and Kubernetes with CI/CD pipelines via GitHub Actions and Jenkins. • Adept at building executive-facing reporting layers using Power BI and Tableau, and collaborating closely with data science, ML engineering, and business stakeholders to deliver AI-ready feature datasets and advanced analytics solutions. • Proven leader and mentor with a track record of guiding junior engineers, establishing coding standards, leading design reviews, and driving delivery consistency across cross-functional data engineering teams operating in Agile/Scrum environments.