Real-time Analytics Pipeline

Scalable data pipeline processing millions of events daily with real-time dashboards.

Client: Fintech Company

Industry: Financial Technology

Duration: 12 weeks

Team: 3 engineers + 1 data analyst

Problem

Legacy batch processing systems couldn't handle growing volume of user events, leading to delayed insights and missed business opportunities.

Solution

Built a modern real-time data architecture using Apache Kafka for event streaming, Airflow for orchestration, DBT for transformations, and BigQuery for analytics.

Approach

Designed event-driven architecture with Kafka
Implemented real-time stream processing
Built automated data quality checks with DBT
Created monitoring dashboards with Grafana

Stack

Apache KafkaAirflowDBTBigQueryPythonDockerKubernetes

Results

5M+ events/day
<100ms latency
90% maintenance reduction