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A robust platform designed to efficiently store, process, and analyze high volumes of transaction data in real time. Built for scalability, resilience, and data integrity, it supports business-critical operations such as reporting, analytics, and system integrations.

Key Features

1. Scalable Data Ingestion
Handles high-frequency transactional input from multiple systems, ensuring real-time data capture without performance degradation.

2. Reliable Storage Layer
Structured storage with schema-based validation using relational and time-series databases, optimized for fast querying and historical tracking.

3. Stream Processing and ETL Pipelines
Data is cleaned, transformed, and enriched on the fly using distributed stream processing frameworks (e.g., Apache Kafka, Apache Flink).

4. Secure and Auditable
Implements encryption at rest and in transit, role-based access control, and full audit logs for regulatory compliance.

5. Integration-Ready
Exposes APIs and data exports to integrate with BI tools, finance systems, and machine learning platforms.

Tech Stack

• Data Ingestion: Apache Kafka, REST APIs

• Processing: Apache Flink, dbt, Python

• Storage: PostgreSQL, ClickHouse or BigQuery for analytics

• Infrastructure: Kubernetes, Terraform, AWS/GCP

• Security: OAuth2, encrypted S3 backups, audit trail logging

This platform enables businesses to make data-driven decisions with confidence while ensuring scalability and compliance.