Position: BigData Engineer
Company: rinftech.com
Experience required: 2y
English level: upper

Необхідні навички
⬥ Java Core, Spring Framework, RESTful services, Microservices Architecture, and patterns
⬥ Java testing frameworks (JUnit, Hamcrest, Mockito)
⬥ Clean Code, SOLID, GoF design patterns
⬥ At least basics and some working experience with SQL DBs; understanding
transactions, ACID, Isolation levels
⬥ Understanding of Big Data concepts, clusters, distributed systems, The CAP
Theorem, replication, fault-tolerance, data locality, batch vs streaming, ETL vs ELT,
cloud, serverless, ... (the more the better :)
⬥ At least some theoretical knowledge and working experience with Hadoop ecosystem
(MapReduce, Hive, Pig, Impala, ...), any distributed processing engine (the best
option — Spark, or others) and NoSQL databases
⬥ Virtualization vs Containerization, Docker, K8s, basics of Linux, command line, at
least basics of CI/CD pipelines, Maven, Git ...
⬥ Apache Beam — would be a big plus

Буде плюсом
● Google AI Hub, Google ML, Tensorflow
● Experience with other stream-processing solutions such as Apache Storm
● Big data querying tools such as Pig, Impala and Hive
● NoSQL Databases such as HBase, MongoDB and Cassandra
● Frameworks such as Flume and different ETL tools
● Big data toolkits such as H2O, SparkML, MapR and Mahout
● GCP Professional Data Engineer Examination certification

Пропонуємо
We place great value on customer focus and innovation. This means that we find it important that you are constantly informed of all developments and techniques within your field and we also encourage this.

⚡️ Possibility to gain great experience in high-loaded international project
⚡️ Ability to grow professionally
⚡️ Friendly atmosphere
⚡️ Comfortable office in Gulliver Business Center
⚡️ Paid vacation/sick leave
⚡️ Medical insurance
⚡️ Gym coverage

Обов’язки
● Contribute to our team’s improvement through honest feedback, but also by leading through example and knowledge sharing.
● Manage implementations of Analytics and ML architecture
● Write readable, testable and fault-tolerant code.
● Review code designs and evaluate new technology.
● Guide team members and other teams on how our tools and products work.
● Ensure solution and operations reliability