Backend Developer @ RTB House in RTB House

As a Backend Developer you will work on the development of tools for configuring, reporting and monitoring advertising campaigns within the RTB (Real-time Bidding) platform.

Tools and technologies used:

• Python, Node.js, TypeScript, Google Cloud, Kubernetes, Docker, Jenkins, PostgreSQL, BigQuery, ElasticSearch, Kafka, Redis, FastAPI, SQLAlchemy, GitHub , Sentry

Example topics:

• Creating a job that calculates aggregates based on raw data
• Development and implementation of a solution allowing for building complex pipelines
• Building a data replication tool using Apache Kafka
• Expanding the system for monitoring resource consumption by users
• Refactoring the API data layer
• Optimize BigQuery queries by using partitioned tables or materialized views

• Python programming experience
• Concurrent and asynchronous programming knowledge
< li> Very good knowledge of relational databases
• Ability to design and implement APIs based on REST or GraphQL
• Knowledge of Linux and containers
• Experience with working on large files data
• Communication skills, ability to work in a team

An additional advantage will be:

• Experience in creating distributed systems
• Knowledge of the Google platform Cloud
• DevOps skills
• Good knowledge of Big Data technologies: BigQuery, Kafka/PubSub

As a Backend Developer you will work on the development of tools for configuring, reporting and monitoring advertising campaigns within the RTB (Real-time Bidding) platform.

Tools and technologies used:

• Python, Node.js, TypeScript, Google Cloud, Kubernetes, Docker, Jenkins, PostgreSQL, BigQuery, ElasticSearch, Kafka, Redis, FastAPI , SQLAlchemy, GitHub, Sentry

Example topics:

• Creating a job that calculates aggregates based on raw data
• Development and implementation of a solution allowing for building complex pipelines
• Building a data replication tool using Apache Kafka
• Expanding the system for monitoring resource consumption by users
• Refactoring the API data layer
• Optimizing BigQuery queries by using partitioned tables or materialized views
[Design and implementation of efficient processes for processing large data sets, Analysis and optimization of the performance of existing systems, Building a system based on data streams, Ensuring the reliability and scalability of the solutions being built, Development of tools that monitor and analyze the operation of the production system, Creation and development of APIs (REST, GraphQL)]
Requirements: Python, concurrent programming, asynchronous programming, SQL, REST, GraphQL, Linux, Google Cloud Platform, BigQuery, Kafka, Pub/Sub, DevOps
Tools: Jira, Wiki, Yes, GIT, Agile, Kanban.
Additionally: Training budget, Small teams, International projects, In-house tranings, Team events, Free coffee, Canteen, Bike parking, Playroom, Shower, Free snacks, Free beverages, In-house trainings, No dress code, Startup atmosphere, Kitchen.