Data
Data Engineering & Integration
EXAGON Data Engineering builds scalable data platforms — lakes, warehouses, and real-time streams — with robust ETL/ELT pipelines and API integrations that unify fragmented systems into a governed single source of truth.
12
Sources integrated
15 min
Sync latency
96%
Data quality score
Single source of truth
Key outcome
Capabilities
Data lakesETL pipelinesAPI integrationMaster data management
Why organisations choose this
- Modern data lake/warehouse architecture on cloud or hybrid
- Automated pipelines with data quality checks and lineage
- API and iPaaS integrations across SaaS and legacy systems
- Master data management for customers, products, and entities
Use cases
01
Enterprise data platform
Snowflake or Databricks lakehouse with 30+ source system ingestion.
02
Real-time event streaming
Kafka-based pipelines for IoT, transactions, and user behaviour events.
03
SaaS integration hub
Sync Salesforce, HubSpot, ERP, and support tools bidirectionally.
What we deliver
Data architecture blueprint
Pipeline implementations
Data quality framework
Integration catalogue
Multi-brand retail data unification
A retailer with 4 brands and 12 systems needed unified customer and inventory data.
Result: Single customer view across brands; inventory sync latency reduced from 24h to 15 minutes.
Ready to discuss Data Engineering & Integration?
Speak with our team about scope, timeline, and fit for your organisation.