We are a product IT company operating in the AdTech industry.
Our product is a high-load programmatic advertising platform that ranks among the Top 3 advertising networks worldwide.
Our scale: 130K+ RPS, with several billion events processed in ClickHouse every day.
Our tech stack: Go, PostgreSQL, Kafka, ClickHouse, K8s.
Who we’re looking for: An experienced backend engineer with strong expertise in Go who is comfortable using a diverse technology stack to solve practical engineering challenges.
Develop and improve the core of our programmatic platform:
- ad selection and targeting;
- statistics collection and delivery;
- advertising event processing;
- ETL processing in a geo-distributed system;
Work on architecture and system design:
- designing system and application architectures;
- designing and developing new backend services;
- replacing legacy system components;
Contribute to and improve our engineering culture:
- developing and improving the codebase of existing applications;
- standardizing and templating boilerplate code;
- conducting code reviews.
- 3+ years of commercial experience with Go;
- Experience designing high-load services based on high-availability principles;
- Experience writing unit tests in Go, with an understanding of what exactly is being tested rather than writing tests purely for coverage;
- Experience with PostgreSQL, including understanding the causes of bloat and how to use the results of EXPLAIN ANALYZE;
- Experience producing and consuming messages with Kafka. Understanding of how to implement exactly-once or idempotent processing;
- Experience deploying applications to K8s;
- Experience optimizing Go code using a profiler and writing benchmarks.
Nice to have
- Understanding of why column-oriented databases such as ClickHouse are used;
- Experience with NoSQL databases (Scylla/Cassandra, Couchbase);
- Experience setting up application observability using Kibana and Prometheus with Grafana;
- Experience configuring GitLab CI pipelines;
- Experience using Debezium to build event-driven systems;
- User-level knowledge of Unix-like systems.
- A competitive market-level compensation package and an open grading system where everyone can see their own and their colleagues’ areas of expertise and growth;
- A clear and streamlined onboarding process with a dedicated mentor;
- An up-to-date and continuously maintained knowledge base in Confluence, along with documentation in MkDocs;
- A collaborative culture and an open, friendly team where everyone is always ready to support and help their colleagues;
- A well-established process for system design (Design Review), development, and code review with minimal bureaucracy.