Data Engineer

Piano is a fast-growing enterprise SaaS company headquartered in New York City, with offices in Slovakia, the United Kingdom, the Netherlands, and Russia. Piano provides enterprise software to leading media companies including Business Insider, The Economist, The Independent, CNBC and others. The software enables media companies to create customized on-site experiences for users, restrict and sell access to content online, and analyze end-user behavior in order to maximize value. 

We are looking for a data engineer to work with our data science and dev-ops teams to create and maintain intelligent machine learning models designed to help our clients to grow their businesses. Piano has billions of behavioral data records from several hundred media sites, hundreds of thousands of subscription and payment records, and a growing set of other customer data at our disposal.  
Our customers are some of the largest international media brands and are seeking ways to better engage their audiences in order to grow their digital businesses. As part of our research team, you will work on cutting-edge prediction models of user behavior that help our customers to achieve their performance goals.

  • Create and manage machine learning pipelines in AWS
  • Work with AWS services such as Amazon SageMaker, s3 and Lambda
  • Build the infrastructure necessary for optimal extraction, transformation, and loading of data 
  • Identify, design, implement, and enhance internal processes
  • Participate in the process of building machine learning models from the ground up, including data exploration, feature generation, model construction, model optimization, and deployment to production
  • Add and improve logging and monitoring to current solutions
  • Collaborate with data scientists and dev-ops engineers to build efficient data products


  • Strong Computer Science and Data Engineering background
  • Strong understanding of database technologies and cloud-based systems/services
  • Experience with building data pipelines
  • Knowledge of machine learning concepts 
  • Experience with cloud based data solutions (AWS preferred)
  • Experience with Python/R and Structured Query Languages 
  • Fluent in English

  • International team based across the globe with an informal culture
  • Subsidised language courses
  • Working from home
  • Flexible hours
  • Laptop
  • Paid Sick days
  • Subsided access to gyms, wellness, and sports centres in Slovakia and Czech Republic
  • Opportunity to learn new technologies and work within the advanced data & data science team
  • Grill parties on company terrace 

Interview stages:
  • Face to face interview
  • On-site assessment

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