A critical near-term initiative is migrating WON deals from the DART legacy quoting system into MongoDB Atlas. DART is one of four CPQ heads (alongside SAP CPQ, CDE, and MPC) feeding the D3 platform. This migration is complex for several reasons:
Data Source Challenges:
- Oracle DB origin: DART's master data resides in Oracle with a traditional relational schema — normalized tables for quotes, line items, pricing, customers, and approvals joined via foreign keys. This must be transformed into a single deeply nested MongoDB document per deal.
- XML export format: DART exports deal data as XML (nightly batch or on-demand trigger for WON quotes). The XML schema does not align 1:1 with the target JSON document model — requiring complex XSLT/programmatic field mapping across 160+ target fields.
- Incomplete data: DART XML exports lack several D3-required fields (SAP material numbers, contract terms, fulfillment details,
billing schedules). These gaps are filled by calling real-time REST enrichment APIs during ingestion:
- TTSAPOUTPUTPKG API
- TTDOSEXTRACT API
Migration Pipeline: DART (Oracle) → XML Export → MuleSoft Validation → S3 Landing Zone → AWS Glue ETL (PySpark) + REST API Enrichment → MDS JSON → S3 Processed Zone → MongoDB Atlas
Required Qualifications
MongoDB Certification (Mandatory) till DATE
Hold at least one active MongoDB certification :
Education & Experience
- Bachelor's degree in Computer Science, Data Engineering, or a related field — or equivalent practical experience.
- 5+ years of skilled experience with MongoDB in production environments, with at least 2 years on MongoDB Atlas (cloud-managed).
- 3+ years designing schemas for complex, deeply nested document structures (not simple flat CRUD collections).
- Experience supporting enterprise-grade workloads — multi-tenant, multi-region, with strict latency and availability SLAs.
📌 MongoDB Architect (India)
🏢 TRISM
📍 India
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