$90k - $120k • 0.10% - 0.25%
Worklytics is a people analytics startup based in NYC and Seattle. We provide our customers real-time insight into Employee Experience by analyzing data on work and collaboration in common productivity tools (G Suite, Office 365, Slack, GitHub, Jira, and more). We combine these data sources with HR systems, engagement surveys, performance reviews and more to discover how team environments and behaviors drive employee outcomes.
Our challenges include processing huge volumes of data about activity across all these tools and using cutting-edge ML techniques to extract actionable insights, while maintaining the highest levels of security and privacy.
Skills: Java, SQL, Software Architecture, Data Analytics, Google Cloud, Git, R, Google App Engine, Data Warehousing, Data Modeling
We're looking for Data Engineers to help us build a revolutionary real-time people analytics platform. You will integrate, process, and analyze large amounts of data on how people work and collaborate within organizations. You’ll build models to answer questions about the skills, productivity and engagement of people and teams.
You should be able to analyze complex problems, navigate large amounts of raw data, and provide actionable insights and explain complicated results in an understandable way. You must be passionate about analyzing data, finding new and interesting ways to visualize results and solving real-world/practical business problems. This is an opportunity to have a huge impact on how companies manage and develop their talent.
What You’ll Be Doing:
- Building data pipelines to ingest, parse, and extract insights from millions of data points on work and collaboration
- Ensuring all data processing is done to the highest levels of security and privacy compliance
- Define new and interesting ways to visualize data and results to make them easy to understand and consume
- Driving your own projects to define new reports and features to be included in user facing products
- Work directly with customers to output and analyze data to solve real internal company issues
What You’ll Need
- Minimum of 2 years experience in quantitative analytics, data science, or software engineering
- B.S. or higher in Applied Mathematics, Statistics, Computer Science, or related quantitative field
- Solid understanding of statistical modeling, predictive analysis, machine learning & data mining
- Experience interpreting complex data and results and presenting them in easily consumable manner to non-technical users (visualizations etc)
- Practical experience with relevant tools and technologies (Java, Scala, R, Apache Spark, SQL)
- Gets-things-done/self-starter attitude. I.e., you can start and drive projects to completion with minimal guidance
Our platform is hosted on Google Cloud (GCP), written primarily in Java 8 on App Engine. We store data in Cloud Storage, Cloud Datastore, and BigQuery. We heavily use SQL in BigQuery for data processing; as well is Pipelines and MapReduce implementations on top of App Engine.
Our web app is Bootstrap / Marionette-based, but we're migrating some pieces to VueJS. Apart from some simple stuff in bash, we script with NodeJS. We use Terraform to define infrastructure-as-code where possible.
We operate minor parts of our platform in AWS / Azure, but see this expanding with the goal to support deploying our platform to these clouds as an alternative in the coming year.