Senior Software Engineer — AI-Powered Analytics Platform

Genesys; Blackrock; Hybrid; EUR 90,000 - 130,000; Full time

Benefits offered by this job

Flexible work options

Career development & growth

Annual bonus program

Comprehensive health coverage

Pension scheme

Job summary

Genesys is seeking a skilled engineer to build and operate AI-powered analytics at scale. You will design highly available services for ingestion, processing, and delivery of analytics data, owning the full lifecycle from streaming to storage.

You will deploy and maintain large AWS environments, mentor peers, and collaborate across engineering, product, and data teams to turn ideas into production-ready capabilities.

Qualifications

• 5+ years of relevant industry experience building and operating scalable, production-grade software systems.
• Strong Java development experience, including Spring and Spring Boot for cloud-native applications.
• Experience with data streaming using Apache Kafka and with real-time data processing.
• Hands-on experience with Apache Druid and/or Apache Flink for analytics and streaming workloads.
• Practical cloud experience (AWS preferred), with familiarity of GCP or Azure welcomed.

Responsibilities

• Build highly available, fault-tolerant services to ingest, process, store, query, and deliver analytics.
• Own the full data lifecycle from streaming ingestion to storage and aggregation.
• Operate large AWS deployments with focus on reliability and performance.
• Collaborate across teams to shape concepts into production-ready tools and services.
• Review code, mentor peers, and help teams solve platform pain points.

Skills

Java development

Spring / Spring Boot

Apache Kafka

Apache Druid

Apache Flink

AWS

GCP / Azure

Distributed systems

Collaboration

Tools

Kafka

Druid

Flink

AWS

GCP / Azure

Terraform

Job description

Genesys is seeking a skilled engineer to build and operate AI-powered analytics at scale. You will design highly available services for ingestion, processing, and delivery of analytics data, owning the full lifecycle from streaming to storage.

You will deploy and maintain large AWS environments, mentor peers, and collaborate across engineering, product, and data teams to turn ideas into production-ready capabilities.