ANKITH MANDUGULA

Company Overview: PNC Bank (Corporate & Institutional Banking), Pittsburgh

• Designed and developed a robust, reusable PySpark-based ingestion framework to onboard diverse partner data sources, improving onboarding efficiency and reducing manual intervention.
• Collaborated cross-functionally with front-end developers, API teams, stakeholders, and solution architects to align technical solutions with business objectives and ensure seamless integration.
• Led the analysis and onboarding strategy for every new third-party data source, streamlining intake processes and establishing reusable ingestion patterns.
• Led technical team in designing and implementing software solutions, ensuring alignment with business objectives and regulatory requirements.
• Mentored junior developers through code reviews and pair programming sessions, fostering skill development and enhancing team performance.
• Engineered fault-tolerant systems that handled large-scale, high-volume datasets with enhanced resiliency and maintainability.
• Generated detailed transformation reports and data quality metrics, enabling better business insights through aggregation and statistical analysis.
• Automated key processes using shell scripting, and supported data model upgrades for evolving analytics and reporting requirements.
• Played a lead role in performance tuning and optimization of environment isolation, resolving package conflicts during Python and library version upgrades.
• Collaborated with scrum masters and business systems analysts (BSAs) to define technical stories, estimate delivery timelines, and contribute to agile sprint planning.
• Continuously enhanced the ingestion framework to support multi-format data ingestion (CSV, JSON, XML, Parquet), improving flexibility for data from vendors like S&P Global and Dun & Bradstreet.

• Designed and maintained enterprise-scale Spark pipelines for ingesting and transforming 3rd-party data into CDI's big data mart, enabling analytics for 200+ tables using Spark, Hive, Python, and Cloudera.

• Led a 5-member offshore team and built a Spark-based marketing data platform from scratch, automating manual workflows and serving as POC for onshore delivery using Spark, HBase, Hive, and Python.

• Developed and optimized Hive/Spark ETL workflows, enabled late-arriving data handling, and contributed to AWS-based Cloudera cluster migration and automation across end-to-end data pipelines.

• Built scalable Hive and Pig-based pipelines for structured/unstructured data analysis, integrating Sqoop, HBase, and MapReduce to generate insights from insurance and web log datasets.