● Professional data engineering experience focused on batch and real-time data pipelines using Spark, PySpark, Python (Scala is a plus).
● Strong hands-on working experience of Big Data stack including Spark and Python(Pandas is a plus).
● Awareness of DevOps.
● Hands-on design and development experience in data space: data processing/data transformation using ETL tools, a data warehouse (data modeling, programming).
● Exposure to Google Cloud and Amazon Web Services.
● Experience working in a high load / high performance distributed project.
● Experience both with async code and with multithreading/multiprocessing.
● Hands-on experience with SQL (e.g. PostgreSQL) and NoSQL databases (MongoDB, Redis, Elasticsearch, etc.)
● An open-minded person who is willing to work in a dynamic R&D environment.
— Experience in one of Python, Java or Scala
— Experience in implementation of Machine Learning
— Experience with developing dashboards and reports
— Strong SQL skills (MySQL, PostgreSQL)
— Knowledge of working with large datasets
— Strong technical, analytical, and mathematical skills
— Intermediate English or higher
Strong mathematical background, keen sense of complexity estimation, a
paranoia for writing efficient code.