19Airline Data Platform – CDC Modernization & Data Mesh
Role: Cloud Solutions Architect
Executive summary
Assessed and redesigned a major airline's first modern Google Cloud data platform, replacing a fragile custom-CDC direction with a managed-CDC decision path and a scalable, event-driven Data Mesh architecture for reliable near-real-time analytics.
- Google Cloud
- Oracle CDC
- Google Cloud Datastream
- GKE
- Dataflow / Apache Beam
- Pub/Sub
- Data Mesh
- Architecture Decision Records
A major airline was building its first modern data platform on Google Cloud to enable near-real-time analytics from mission-critical Oracle systems. The initial design used custom CDC ingestion built with Spring Boot and Quarkus applications on GKE, creating scalability, maintenance and data-consistency risks.
- Evaluate the proposed ingestion strategy and identify the operational risks of custom Change Data Capture (CDC).
- Assess a more scalable managed-CDC approach and document the trade-offs for stakeholder alignment and governance.
- Design a future-proof architecture capable of moving data reliably and consistently for enterprise-wide analytics.
I performed the architecture assessment, researched Google Cloud Datastream and authored an Architecture Decision Record (ADR) comparing the custom Java ingestion with native cloud CDC. I redesigned the proposed flow around Datastream and worked with database and platform teams on Oracle prerequisites. When the Oracle team could not accommodate the required database changes and restart, I designed a V2 based on Data Mesh principles instead of forcing an unworkable dependency. The event-driven design used Dataflow (Apache Beam), Pub/Sub and domain-oriented data products, with explicit validation, ordering and consistency controls to address reliability problems in the Spring Boot approach.
The redesigned controls reduced data-reconciliation effort by approximately 60% and cut analyst and engineering rework related to query corrections and data validation by an estimated 40%. The V2 roadmap supported new domains without major platform redesign, improved resilience, reduced dependence on custom CDC maintenance and established reusable architectural standards for future engineering decisions.
Successful data-platform adoption depends as much on organizational constraints as technical capability. This work deepened my expertise in enterprise CDC and its operational dependencies, reinforced ADRs as tools for alignment and governance, and gave me practical experience applying Data Mesh principles while balancing database, platform and business requirements.