We are looking for a Senior Data Engineer with deep expertise in Java, Kafka, Flink, and large-scale streaming data platforms to implement core components of Employee Experience. This is a hands-on engineering role focused on building high-quality production systems across distributed backend services, high-throughput streaming pipelines, and complex data processing. The engineer will work from architectural direction and product requirements, turning designs into reliable, maintainable, and scalable implementations. We are looking for someone with proven experience building, scaling, and operating high-volume production systems, who understands the architectural and operational complexities of real-world scale. Someone who can take ownership of complex engineering tasks, make sound implementation decisions, identify risks early, and deliver robust solutions with minimal supervision. Strong experience with modern AI and agentic coding tools is an important part of the role.
Responsibilities:
- Build production-grade Java services and high-throughput data-processing components based on defined architecture and product requirements.
- Develop, optimize, and maintain large-scale streaming pipelines using Kafka and Apache Flink.
- Integrate data from multiple products into a unified pipeline and organizational data model.
- Build services and APIs using Java, TypeScript, gRPC, and Protobuf.
- Design and implement persistence solutions using PostgreSQL, ClickHouse, and Redis.
- Write and optimize complex queries, schemas, indexes, and data-access patterns for massive datasets.
- Develop frontend capabilities using TypeScript and React when needed.
- Implement employee, department, device, and RBAC-related functionality.
- Improve system scalability, reliability, throughput, latency, observability, and operational cost.
- Diagnose and resolve production bottlenecks across distributed streaming pipelines, services, and databases.
- Collaborate with architecture, product, and DevOps teams to turn designs into maintainable production solutions.
- Use AI-assisted and agentic development tools effectively while maintaining high standards for correctness, security, and code quality.
Requirements:
- Engineering experience: 10+ years building and maintaining production systems, including significant hands-on experience designing, scaling, and operating distributed, high-throughput data platforms.
- Java: 5+ years of professional Java experience, including building and optimizing high-performance, production-grade data-processing systems. Strong understanding of concurrency, memory management, and JVM performance tuning.
- Apache Kafka: 3+ years of hands-on production experience with Kafka, including partitioning, consumer groups, schemas, delivery guarantees, fault tolerance, and performance tuning at high throughput.
- Apache Flink: 2+ years of hands-on production experience with Flink, including stateful processing, windowing, checkpointing, state management, backpressure, fault recovery, and large-scale pipeline optimization.
- Large-scale systems: Proven experience designing, building, scaling, and operating systems processing millions of events per minute. Deep understanding of distributed-system bottlenecks, throughput, latency, resource utilization, and operational efficiency. Demonstrated personal ownership of complex production challenges and scaling decisions.
- Databases and optimization: Strong experience with working with time-series data and large-scale analytical databases, including data modeling, query optimization, partitioning, and efficient ingestion of high-volume data. Experience with PostgreSQL or other relational databases.
- APIs and data contracts: Experience with Protobuf, schema evolution, and compatibility in distributed systems. Familiarity with gRPC and service-to-service communication.
- Production operations: Hands-on experience deploying, monitoring, troubleshooting, and optimizing distributed production workloads. Good understanding of Kubernetes, CI/CD, observability, resource management, and production incident resolution.
- AI and agentic coding: Strong hands-on experience using AI-assisted and agentic coding tools to design, implement, test, debug, and refactor production systems. Ability to critically review AI-generated code for correctness, security, maintainability, and production readiness.
- Engineering ownership: Ability to independently own complex technical components, evaluate architectural tradeoffs, identify performance and reliability risks, and deliver robust, maintainable production solutions with minimal supervision.
- DevOps: Good familiarity with CI/CD, Docker, Kubernetes, and observability, including practical experience troubleshooting and operating production workloads.
Benefits:
- English courses
- Health insurance
- Sport compensation
- Psychologist compensation
- Discount program
- Corporate events and team building
- Corporate library
- Remote work options
- Flexible working hours
- Activities in the office- kicker, table tennis, PlayStation, music room
