Big Data Verticals

We have several teams extremely focused on building data as a product.  This starts with building large scale data pipelines to produce foundational datasets the entire company uses to power everything from the Economic Graph to our cross company intraday business metrics. Beyond this, we’re also working with and providing tooling that enables our partners to quickly meet their own data needs.

Big Data Integration

Our data ecosystem ingests and exchanges data with a broad variety of partners and systems. This team focuses on scaling data integration in a secure manner by building standard services and libraries that enable built-in high availability, compliance, and rapid deployment. 

Data Management & Compliance

This team leads data privacy and compliance engineering for our big data ecosystem.  We lean heavily on a platform that not only monitors for data issues, but also actively detects potential risks. By employing data engineering, machine learning, and back-end software development, as well as partnering with security and legal organizations, we ensure LinkedIn remains members-first.

Getting to know: Chiranjeevi Devi

LinkedIn wouldn't be the company it is today without the engineers who built it. Meet Chiranjeevi Devi, a senior software engineer at LinkedIn, who works on some of the toughest challenges around big data.
 

Data Management & Compliance

LinkedIn is a members-first company and we strive to maintain our members trust by enforcing security and privacy controls across our data systems.

Espresso

Espresso is LinkedIn’s horizontally scalable document store for primary data such as member and company profiles, InMail, social gestures (likes, comments, shares) various advertising data sets, etc.

WhereHows

WhereHows is a central metadata repository for the processes, people, and knowledge around the most important element of any big data system: the data itself.

Data Integration

Our data integration team aims to unify and leverage the Gobblin ecosystem for seamless inter-company and intra-company data exchange.

In the News: Open-sourcing WhereHows

A look back at when we open-sourced WhereHows in 2016.

Video: WhereHows: Taming Metadata for 150K Datasets Over 9 Data Platforms

A WhereHows presentation from a 2017 Big Data meetup.

Voices: a Text Analytics Platform for Understanding Member Feedback

While it is clear that such member feedback, or “Voice of the Member” (VOM), contains valuable information, it is often less clear how to best analyze such data at scale.