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AWS, Python, GoLang, Cloud9, GitHub, ELK, Cloudera

We use Golang for our backend, Typescript and React for our web client, GraphQL to fetch data from our backend, and React Native for our mobile app. Direct experience with these technologies is not required.

Backend: Node + Express, Typescript, Go Microservices. Frontend: Next.js, React + Hooks, Storybook. Infrastructure: Heroku + AWS, CircleCI, DataDog.

Web stack: Django, GraphQL, React, Postgres. Data pipeline: Spark, Kafka, Elastic Search, Scala. Infra: AWS.

React, MySQL, Java, MongoDB, Redis, Amazon S3, Go, Amazon RDS, Swift, Objective-C, Kafka, Scala, Cassandra, Amazon DynamoDB, Kotlin, Apache Spark, Amazon Redshift, gRPC, Amazon Redshift Spectrum, Elasticsearch, Mixpanel, TensorFlow, GitHub, Jenkins, Webpack, Kubernetes, Datadog, Terraform, Chef, Crashlytics, Bazel, Envoy

Backend: Ruby on Rails, Postgres, Elasticsearch, Google Cloud Platform, Kubernetes

Frontend: Typescript, React, Redux

Data: BigQuery, BigTable, DataFlow, DataProc

Rails, MongoDB, Knockout, Go, AWS

Ruby on Rails, Elixir, React.js, GraphQL, Node.js, AWS, Redis, Spark & Scala (Data team)

Outside of our data teams, our engineering teams use Java, JBoss, CDI/Spring, Freemarker, Jquery, Knockout, SpringBoot, Redis Kinesis, Docker.

Our Data Engineering team uses Groovy, Redshift, AWS Data Pipeline, AWS Lambda, Cassandra, AWS Elastic Bean Stalk, Python, Docker.

Our Data Science team uses Python, Jupyter Notebook, SciKitLearn, Redshift, and Docker.

Cloud Foundry on AWS for hosting all servers, Akamai CDN, Java 8/Kotlin used on all backend services and APIs, RDS (AWS MySQL) used for account data storage, AWS S3 used for raw storage, RedShift used for analytics, React.js used for web based front end clients (including dashboards), Swift for iOS, Kotlin for Android, Python for Data Science

Airtable’s core stack is written using JavaScript, augmented with static type checking and other tools. We use Node.js on the backend, and mostly-React on the frontend, but our application requirements drive a substantial amount of custom software architecture; that is, Airtable is pretty far from a boilerplate “React + Express” application. We also periodically evaluate adding other languages into our codebase for ecosystem or performance reasons. Mobile apps are currently written in the standard platform language, mixed with JavaScript in webviews where appropriate. Our production infrastructure runs on a variety of AWS services, principally using Terraform for deployment; for data collection, aggregation, monitoring, and alerting, we use a mixture of ELK and some carefully selected third-party services.

Frontend: express, react, redux, bootstrap

Middleware: express

Backend: everything but dominantly GoLang running on AWS

Across our product portfolio we leverage a variety of languages, frameworks and tooling. Much of our code is written in C#/.NET Core 2.x along with a handful of other languages such as C++, PHP, Node.js and Java. For frontend, Angular 6+ on the newer products, and a few mature products leveraging Javascript and JQuery. Many databases to store our 300TB+ of production data including MySQL, SQL Server, MongoDB, Snowflake, DynamoDB & RDS. We have some monolithic applications though new products & platforms are built using microservices running Docker containers on AWS ECS with some footprint in Azure. We leverage many AWS services – Lambda, CloudWatch, S3, EC2, Route53, IAM, SQS, SNS and more. We also use Terraform for configuring infrastructure, Jenkins for CI, and Git/GitLab for source code. These are flexible (they can and will change) and what a candidate knows for stack is not as important as their ability to think creatively – we can train languages, it’s much harder to train curiosity and intellectual drive.

The bulk of our infrastructure is dedicated to distributed processing for machine learning, powered by Apache Hadoop: Hive, Presto, and Spark. Our web app uses React on the frontend and Ruby on Rails on the backend. We’re hosted on AWS.

Frontend: React, Relay, Flow, Jest, Enzyme

Mobile: React Native, Apollo

Backend: Ruby on Rails, Postgres, GraphQL, Python, RSpec

CI: GitHub, Buildkite

Infrastructure: AWS, Python

Backend: Ruby on Rails, Frontend: ReactJS

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Web - Node, React, Python, PostgreSQL

Mobile - React Native, Swift (iOS) / Java (Android)

Golang, React, Redux, MongoDB, ElasticSearch, Redis, HAProxy, NATS, Kafka, Redis, and Cassandra

Blog Post on our Tech Stack

Lever uses our own open source MVC framework called Derby that syncs all data via Operational Transformation (the algorithm behind Google Docs). OT is the way we handle concurrency conflicts for any piece of data that is edited at the same time. In addition to real-time sync, OT allows us to provide a smoother UI since we can render updates on the client instantly without waiting for our backend to respond, while still guaranteeing consistency.

Lever makes extensive use of AWS, Docker, Node, Mongo, ElasticSearch, and Redis within our infrastructure. We use tools like Hubot to streamline deployments and Grafana to see what’s going on under the hood. In addition to automating all the things, we love to version them too! Our systems are all created using Terraform and Chef, working together to ensure consistency at all costs.

Node.js, React.js, Redis / Mongo, AWS, Kubernetes / Terraform / Docker

Ruby, Rails, Javascript, React, MySQL, Kubernetes

Ruby on Rails

Swift

Postgres

Redis

Memcache

RabbitMQ

AWS

Heroku

Ruby on Rails, React, Redux, React Native, Backbone, Apollo, GraphQL, Redis, ElasticSearch, Postgres, Heroku, Airflow, Python 3

Ruby / Javascript / Python / Golang

Sinatra / Rails / React

MySQL / Mongo

Presto for data warehouse

Docker / Kubernetes for deployment

REST / JSON / gRPC for service communication

TypeScript, JavaScript, and React

Scala (high performance backend)

Python (infrastructure management and data analysis)

Android and iOS

Luna1 (legacy in-house functional reactive framework, similar to Meteor)

Frontend: React/Redux. Legacy JSP (although increasingly less!)

Monolith backend: Java on Tomcat.

Microservices backend: Java on Spring.

API: Java w/ Swagger.

TechOps: Hashicorp stack + Docker on EC2/AWS. Cloudflare, EBS, Redis. Git/GitHub for Source Control. Jenkins for CI. Ruby/Cucumber for testing.

Databases: MySQL

Search: SOLR

Data: Python (pandas, AirFlow, etc.). Redshift/Postgres.

OnForce Platform (subsidiary): PHP on baremetal LAMP (deprecating, moving to AWS).

Languages/Frameworks: Angular, Node, Serverless Lambda, Rails, Coldfusion

Databases: MSSQL, Aurora

Cloud Providers: AWS

React, Redux, Node, Java, Postgres, AWS

Our main app is a Ruby on Rails API, with a Postgres and PostGIS database and a front-end built using React.js. It’s hosted in Heroku. We also have a variety of services built in Python that are hosted on AWS.

We’re primarily a Python shop, using Django for our websites. We also have a few services written in Go and have started to build out our front ends using React. We use Github to host our code, Jenkins (for now) to automate our tests, and right now most of our applications and code live in VMs in a Colo just outside of Toronto. We’re in the process of transitioning to AWS. Other common technologies we use are Postgres (primary DBs), Redis (cache and key/value store), RabbitMQ (messaging broker) and Celery (task queue).

React Native, React, Ruby on Rails, Go

JavaScript/CoffeeScript, Python, Node.js, React + React Native, AWS Lambda, Spark, Kinesis, MongoDB, Redshift

Python / Django Scala Golang Postgres Cassandra ElasticSearch Redis AWS (EC2, S3, ALB, EBS, Kinesis, SQS) Linux (Ubuntu)

Tech stack varies from team to team: PHP, React, Java, Node, Scala, Objective-C, Go, etc.

AWS rds + mysql for data storage API is in python + flask apache thrift for interface definition android app is in java ios apps in swift 3 front-end web is in python, flask, node, and react

ASP.NET / C# / MVC 4+ / LINQ / AJAX / JavaScript / jQuery / JSON / SQL / T-SQL / XML / XSL / XPath / XHTML / DHTML / CSS / Bootstrap / Rest / SOAP / Web Services