By Pavani Chada, Data Product Manager, PayPal

Modern finance is in the middle of a profound transformation—and it begins at the data layer. With rising customer expectations, global transactions, and real-time settlements, payment companies are rethinking how financial data is processed, reconciled, and governed. In her session at SheForSTEM, Pavani Chada, a seasoned data and technology leader with over 20 years of experience across data engineering, architecture, and product management, shared how metadata-driven and cloud-native infrastructure is reshaping financial systems at PayPal.

Financial data ecosystems are complex, especially in a global payments environment. Transaction information originates from multiple sources—PayPal, Braintree, Venmo, and other upstream platforms—while processors like Fiserv and banks send separate settlement and BAI files. Finance teams must align all these streams flawlessly every single day. Legacy systems rely heavily on batch jobs, rigid pipelines, slow processing, and manual reconciliation, leaving finance teams burdened by delays and limited visibility.

Pavani described how PayPal’s shift from legacy Hadoop systems to Google Cloud Platform (GCP) marked a turning point. In a cloud-native world, systems are elastic, scalable, and built for real-time data movement. The real magic, however, lies in a metadata-first approach—where every transaction is enriched with contextual, accounting, and compliance metadata before entering analytical or consumer-facing systems. This makes transactions self-describing, auditable, and finance-ready from the start.

The impact of this transformation has been significant. Automated, rule-based reconciliation has cut manual efforts by more than 80%. Month-end closes that once took days now finish within hours. System reliability has reached near-perfect levels, even during peak seasons. Finance dashboards show real-time mismatches, anomalies, and ledger summaries, allowing accounting, reporting, and compliance teams to make decisions instantly instead of waiting for batch cycles.

Another critical advantage is compliance by design. With metadata-enriched events, immutable logs, and complete lineage, frameworks such as SOX and GLBA are inherently supported. Instead of reacting to compliance issues late in the audit cycle, risks are detected and addressed continuously. Every adjustment, exception, or correction is traceable—building trust with auditors and regulators.

Pavani also highlighted the architectural backbone that enables all of this: canonical data models, domain-oriented microservices, real-time streaming pipelines, and zero-trust security. These systems support faster product rollouts, simplified rule management, and cleaner integration with downstream consumers like FP&A and Treasury. The transition wasn’t without challenges—teams needed reskilling, auditors needed convincing, and security controls had to evolve—but strong collaboration across finance, tech, and compliance made the journey possible.

Looking ahead, PayPal’s finance data platform is moving toward serverless operations and AI-driven anomaly detection, pushing automation even further. Machine learning models will soon flag mismatches, fraud patterns, and compliance risks in real-time, making finance operations proactive and predictive.

Pavani closed the session by emphasizing how real-time ingestion and metadata-driven workflows empower leadership with instant, accurate insights. In a world where financial accuracy and transparency are non-negotiable, cloud-native architecture is not just a technical upgrade—it is a strategic transformation that strengthens trust, improves resilience, and accelerates innovation.

Her journey is a testament to what is possible when technology, finance, and data engineering converge with a strong vision. At SheForSTEM, we celebrate Pavani’s leadership and her role in shaping the future of financial data infrastructure.