We are looking for a Backend / Distributed Systems Engineer to design, scale, and maintain high-throughput ingestion microservices, streaming pipelines, and edge-to-cloud data synchronization platforms. You will tackle engineering challenges ranging from sub-second sensor telemetry ingestion to predictive maintenance data pipelines and automated data quality validation across a globally distributed, edge-heavy infrastructure.
Edge-to-Cloud Ingestion & Streaming Pipelines: Design, build, and scale high-throughput, low-latency microservices using Golang, RabbitMQ, and Kafka to reliably ingest high-volume time-series telemetry and machine data from edge devices under variable network conditions.
High-Performance Endpoints & Data Modeling: Implement resilient REST and gRPC API endpoints for time-series sensor ingestion, asset tracking, and state monitoring, persisting transactional data in PostgreSQL and analytical data in Snowflake.
Edge System Integration & Synchronization: Build fault-tolerant synchronization services, local buffering, and network retry mechanisms to ensure zero data loss between distributed edge stations and centralized cloud services.
Automated Data Quality & Governance Framework: Architect an automated data quality pipeline featuring real-time schema validation, anomaly detection, deduplication, and dead-letter queue (DLQ) processing across message queues.
Software Version & Asset Governance: Build microservices and auditing layers to track, verify, and enforce station software versions, firmware baselines, and configuration drift across distributed environments.
Site Reliability & Operational Automation: Develop automated health-checking mechanisms, self-healing recovery workflows, and operational runbooks; instrument services with Prometheus and Grafana to ensure 99.99%+ availability across all production environments.
EU flexible schedule (9-18 CET);
Weekly customer meetings between 17-20 CET.
Short Bytex HR introductory discussion;
1-2h Bytex technical discussion with one of our senior engineers;
Customer call;
Offer presentation.
If you want to apply for this position, please fill in the form or send us an email at *******.
Bachelor’s or Master’s degree in Computer Science, Distributed Systems, or related engineering discipline.
5–10 years of hands-on software engineering experience building scalable backend microservices, data pipelines, and edge-connected systems.
Strong proficiency in Golang, with solid secondary experience in Python, Java, or Rust.
Deep hands-on experience with message brokers and event streaming: RabbitMQ and/or Apache Kafka.
Proven experience building and scaling ETL / data pipelines feeding cloud data warehouses like Snowflake.
Solid background in relational data modeling and query optimization with PostgreSQL.
Experience with edge-based architectures, including edge-to-cloud data sync, offline buffering, and network resiliency patterns.
Deep understanding of distributed systems principles: partitioning, message idempotency, backpressure, retry strategies, and eventual consistency.
Production experience with Linux/Unix environments, Docker containerization, and orchestration via Kubernetes.
Deep experience optimizing Snowflake schemas, clustering, data sharing, and ingestion pipelines (e.g., Snowpipe).
Experience with gRPC, Protocol Buffers (Protobuf), and high-performance RPC protocols.
Experience with metrics and observability stacks (Prometheus, Grafana, OpenTelemetry) and chaos engineering practices.
Knowledge of industrial IoT protocols, hardware test station communication, or time-series data handling.
Familiarity with applying GenAI/LLM-assisted workflows for automated log analysis, triage, and runbook execution.
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