Data Engineering

Event-Driven Data Processing

A real-time event processing pipeline turning streaming business events into structured, analytics-ready data.

Azure Event HubsDatabricksPySparkDelta LakePython

The Problem

A data-intensive application needed to reliably ingest and process continuously arriving events without creating processing bottlenecks as event volume increased.

The Solution

We built streaming pipelines around Azure Event Hubs and Databricks, using PySpark for distributed processing and Delta-based storage. Spark transformations were tuned for high-volume streaming workloads to improve processing efficiency.

Results

Streaming

Ingestion

PySpark

Processing

Databricks

Platform

Technology Stack

Azure Event Hubs

Databricks

PySpark

Delta Lake

Python

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Let’s build the right solution.

Whether you’re modernizing an existing platform, building a new product, or scaling your data and cloud infrastructure, our engineers can help turn complex requirements into reliable technology.

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