# Inside Data Engineering at Doximity: Building for Impact

DevFeed: [Inside Data Engineering at Doximity: Building for Impact](<https://devfeed.tech/articles/inside-data-engineering-at-doximity-building-for-impact-20032.md>)

Original publisher: [Read original article](<https://technology.doximity.com/articles/inside-data-engineering-at-doximity-building-for-impact>)

Author: Doximity

Published: 2025-08-20T15:29:00Z

Content type: article

Language: en

Sources: [Doximity](<https://devfeed.tech/sources/doximity.md>)

Topics: [data-engineering](<https://devfeed.tech/topics/data-engineering.md>), [data](<https://devfeed.tech/topics/data.md>), [coding](<https://devfeed.tech/topics/coding.md>), [SQL](<https://devfeed.tech/topics/sql.md>)

Tags: [coding](<https://devfeed.tech/tags/coding.md>), [data-engineering](<https://devfeed.tech/tags/data-engineering.md>), [engineering](<https://devfeed.tech/tags/engineering.md>), [pipelines](<https://devfeed.tech/tags/pipelines.md>), [sql](<https://devfeed.tech/tags/sql.md>), [systems](<https://devfeed.tech/tags/systems.md>)

## AI overview

This article explains how Doximity organizes data engineering into platform-focused and product-focused roles. It describes the teams' responsibilities, daily engineering practices, and how product data engineers use pipelines, queries, and data sources to support product development and user value.

## Source excerpt

IBM defines Data Engineering as "the practice of designing and building systems for the aggregation, storage, and analysis of data at scale, empowering organizations to get insights in real time from large datasets." While this definition generally captures what data engineering is, it blends together distinct specializations that enable scalable transformation of raw data to actionable insights. At Doximity, we break this down into two distinct roles: product-focused data engineers and platform-focused data engineers, each playing a crucial role to fuel our organization with timely, reliable data. Our platform-focused data engineers sit on a centralized team that owns two core areas: (1) providing a high-velocity, low-risk data platform and (2) providing reliable and accessible services, standards, and foundational datasets. Our product-focused data engineers are embedded directly on product teams and leverage our data platform, its services, and data to shape our products and deliver value directly to our users. Let's take a closer look at a day in the life of our product team data engineers. Finding Flow As a member of a cross-functional product team, mornings typically start with a quick scrum (sometimes live, sometimes asynchronously in Slack), providing a shared space to align priorities and highlight blockers before diving into focused work. Meetings are minimal; most of the day is spent deep in the code, refining data pipelines, optimizing queries, reviewing code, and working closely with the other members on your team. We are first and foremost engineers, and take pride in spending as much time as possible doing what we love: coding. This includes everything from small snowflake SQL logic tweaks to systemic architecture designs. The goal isn't only to move data but also to ensure that every system we build remains maintainable for fellow engineers and intuitive for analysts. It's no wonder that one of our guiding principles is "Always leave the code better