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Centralised Data Lake for Real-Time Analytics
A leading global hedge fund needed to consolidate data from dozens of external systems into a single, real-time data lake. Fragmented data sources were creating latency and inconsistency in analytics.
Disparate data sources across on-premises SQL Server and cloud-based Snowflake databases required a unified ingestion framework. Existing batch processes could not keep pace with the demand for real-time analytics and reporting.
Designed and deployed an extensible data pipeline using Apache Kafka for real-time streaming and Apache Airflow for orchestration. Built a centralised data lake with Snowflake, deployed serverless REST APIs on AWS Lambda, and containerised micro-services with Docker and Kubernetes. Infrastructure was managed entirely through Terraform.
Data consolidated into a single source of truth — enabling real-time analytics that were previously impossible.
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