The client is a leading cloud-based energy technology company that partners with utilities, energy retailers, and power producers worldwide, serving 120+ energy providers globally. Its AI-powered platform drives customer engagement, grid flexibility, and clean energy outcomes while accelerating the transition to a more resilient and sustainable energy ecosystem.
The client recognized the need to modernize its data pipelines to ensure future readiness, operational efficiency, and stronger governance. Its objectives were to:
- Modernize legacy Matillion-based ETL/ELT workflows to improve scalability, performance, and long-term sustainability.
- Standardize data processing across multiple clients while handling diverse data formats.
- Accelerate pipeline migration and refactoring with minimal manual effort and reduced operational risk.
- Enhance data governance with improved lineage visibility and role-based access controls.
- Enable scalable, high-performance pipelines capable of supporting advanced analytics and reporting.
- Optimize ETL platform costs by transitioning away from expensive legacy licensing models to a consumption-aligned data engineering platform.
Cybage designed a modern Databricks Lakehouse-based data platform to replace the legacy Matillion ETL workflows. This solution enabled scalable, governed, and high-performance data pipelines, accelerating the client’s modernization journey.
- We implemented an optimal ingestion and transformation strategy using Delta Live Tables and custom Spark jobs to handle both declarative and complex business logic.
- Our team accelerated legacy ETL modernization using the Databricks GenAI Assistant to convert Matillion workflows into optimized PySpark and SQL, reducing manual effort and migration risk.
- We helped the client adopt the Medallion Architecture (Bronze–Silver–Gold) to standardize data processing workflows, enhance data quality, and deliver analytics-ready datasets for downstream consumption.
- Our experts automated ETL orchestration and scheduling using Databricks Notebooks and Jobs to ensure reliable and repeatable pipeline execution.
