helpshift-engineering

How Data Powers Agent Productivity

As a data engineer, I used to see metrics as just numbers on a dashboard — until I realized they’re the lens through which customers view…

Using Clojure channels to increase throughput

When building systems that process large volumes of messages synchronously, performance bottlenecks can quickly become a challenge…

Building a Centralized Alerting Framework for Data Quality Monitoring and Incident Management

Load Testing API’s on Redshift & Snowflake — A Quick POC

Overview

Migrating from a Monolithic Orchestrator to Apache Airflow

Before we knew better

Breaking the Ice: Integrating Snowflake with Power BI

A simple guide on how to connect Snowflake data in Power BI to create reports, publish them, and schedule refreshes.

Form Validation Tips Every Web Developer Should Know!

Discover 13 practical tips to make form validation seamless, user-friendly, and accessible for the best user experience.

Why Mentorship Matters? Beyond Tasks and Deadlines

In every growing organisation, mentorship quietly powers progress. It’s not just about reviewing work or assigning tasks but it’s about…

From Data to Insight: Helpshift’s Journey with ML Observability

How a Wide Events-Driven Logging Approach Powers Effective, Scalable, and Cost-Efficient ML Observability

One in a Million Ways to Detect Customer Churn — Powered by Pure Metric Engineering

A real-world case study on building a Churn Intelligence Framework using revenue dynamics, structured KPI design, and behavioral transitions

The Hidden Layer of Analytics: How QA Builds Trust in Data

Every accurate metric is backed by countless validations, events checks and integrity tests in the background.

Agile vs. Waterfall QA: A Comparative Guide

Quality Assurance (QA) is a critical aspect of software development, ensuring that the final product meets the desired standards and…