Modernising a Legacy Data Transformation Platform

A global pharmaceutical company was relying on an aging Informatica-based data transformation platform that had become increasingly difficult to maintain, govern, and scale. As data requirements expanded, the legacy architecture slowed analytics delivery and created additional challenges around model management, governance, and production support.

Nexint AI Solutions modernised the transformation layer by migrating the existing Informatica workloads to a scalable dbt-based data transformation framework, while ensuring business-critical pipelines continued operating without disruption.

The Challenge

The existing platform presented several operational and development challenges:

Legacy Informatica workflows increased maintenance complexity.
Data models were difficult to standardise across multiple domains.
Analytics teams faced slower delivery cycles.
Governance and reusable development patterns were limited.
Existing production pipelines required uninterrupted availability during migration.

The objective was to introduce a modern transformation architecture without compromising existing business operations.

Our Solution

We designed and implemented a structured migration approach that moved transformation workloads from Informatica to dbt while improving the overall development and governance framework.

Our team handled the end-to-end solution design, data model review, migration, testing, deployment, and productionisation.

Key Implementation Areas

Modern Data Transformation with dbt
Existing transformation logic was redesigned and converted into modular dbt models, creating a more maintainable and scalable transformation layer.

Data Model Modernisation
Models across multiple business and data domains were reviewed, redesigned, and standardised to improve consistency and reusability.

Governance & Reusable Patterns
SnapLogic governance standards were established alongside a reusable pattern asset library, helping teams follow consistent integration and development practices.

Workflow Orchestration
End-to-end pipeline orchestration was architected and delivered using Apache Airflow, enabling reliable scheduling, dependency management, and monitoring.

Delivery Approach

The migration was executed through a controlled process covering:

Architecture and solution design
Informatica workload assessment
dbt model development and review
Data validation and testing
Airflow orchestration
Governance implementation
Production deployment and support

Business Impact

The modernised platform created a stronger foundation for analytics and data engineering by improving transformation maintainability, governance, orchestration, and scalability—all while maintaining continuity across live production pipelines.