Data Engineer

Time zone

(GMT+3), Minsk.

Loóna is constantly growing and evolving:

• 1.5M+ downloads.
• 215k+ MAU.
• 6.7M mindful minutes that users spend with Loóna every month.
• The 2021 Apple Design Award winner.
• Google Best App of 2020 winner.
• Featured in Vogue, Forbes, Techcrunch, CNN, and more.
• Loóna’s investors include: Natalia Vodianova, Elefund, Hoxton Ventures, Elysium, Matthew Freud, Mark Vranesh, Michael Antonov, and Palta.

What you will do

• Work with ML team to supply their demands in data.
• Create optimal data pipeline architecture.
• Assemble large, complex data sets that meet functional / non-functional business requirements.
• Build the infrastructure required for optimal extraction, transformation, and loading of data from a wide variety of data sources using Apache Spark and other big data technologies.

Who you are

• Experience building and optimizing big data data pipelines, architectures and data sets.
• Advanced knowledge of SQL and experience working with relational and non-relational databases.
• Experience with Spark (especially PySpark).
• Experience with data pipeline and workflow management tools, e.g. Airflow.
• Advanced knowledge of Python and ability to code on it (many pipelines will require not just moving data from one place to another, but also scraping them from websites and parsing data from scraped text in to relational data format).
• Ability to dive into complicated busines domains.
• Ability to map business processes on how the data is stored in the databases.
• Strong analytic skills related to working with unstructured datasets.
• Great attention to details: it is critically important that the candidate always verifies the data quality: he must be accustomed to writing tests for row counts, for count of distinct entities, etc. In other words: data engineer is fully responsible for the quality of data processed by his jobs.
• Ability to be a DevOps for himself: the candidate must be able to at least set up a Standalone Spark cluster on a Linux box for his development purposes.

It will be preferable (but not required) if:

• The candidate has experience with mobile domain industry.
• The candidate worked with such things as Amplitude, Appsflyer, Revenue Cat, Firebase and has domain knowledge of what is happening on a mobile device and how this information flows up.
• The candidate worked with Docker and has some devops skills (to be able to deploy his pipelines to production).