/ TEAMS · Specialist engineering · Apache Flink
Source engineers experienced in Stream processing, stateful applications and operational pipelines. for business-critical production systems, safe integrations and measurable technical ownership.
2,000+ engineers in our active talent network · Regional recruiters
/ SYSTEM STACK
DataStream API
state backends
watermarks event time
exactly-once checkpoints
Kafka connectors
/ AVAILABLE TO HIRE
Profiles show the experience we can source. Individual candidate availability is confirmed after enquiry.
Mid+ Apache Flink Engineer
Inquire availability5+ years of experience · Serbia
Apache Flink Engineer with 5 years in production systems, focused on DataStream API and state backends.
Languages: Serbian, English B2+
Senior Apache Flink Engineer
Inquire availability7+ years of experience · Montenegro
Apache Flink Engineer with 7 years in production systems, focused on state backends and watermarks event time.
Languages: Montenegrin, English B2+
Senior Apache Flink Engineer
Available10+ years of experience · Serbia
Apache Flink Engineer with 10 years in production systems, focused on watermarks event time and exactly-once checkpoints.
Languages: Serbian, English B2+
Mid-level Apache Flink Engineer
Inquire availability3+ years of experience · Lithuania
Apache Flink Engineer with 3 years in production systems, focused on exactly-once checkpoints and Kafka connectors.
Languages: Lithuanian, English B2+
/ Engineering teams
Onectus uses its active engineering network and regional recruiting partners to search against concrete systems, environments and responsibilities. We evaluate practical experience rather than treating a framework mention or certification as proof of delivery. Particular availability and engagement terms are confirmed after an enquiry. For this role, practical knowledge of DataStream API, state backends, watermarks event time helps define the engineering search.
/ Technical specializations
The right profile depends on your actual architecture, performance constraints, integration boundaries and operational responsibilities.
Apache Flink responsibilities include datastream api, related state backends, clear test coverage and a reliable production handover. Examine the actual tooling and deployment environment.
Apache Flink responsibilities include state backends, related watermarks event time, clear test coverage and a reliable production handover. Examine the actual tooling and deployment environment.
Apache Flink responsibilities include watermarks event time, related exactly-once checkpoints, clear test coverage and a reliable production handover. Examine the actual tooling and deployment environment.
Apache Flink responsibilities include exactly-once checkpoints, related kafka connectors, clear test coverage and a reliable production handover. Examine the actual tooling and deployment environment.
Apache Flink responsibilities include kafka connectors, related savepoint upgrades, clear test coverage and a reliable production handover. Examine the actual tooling and deployment environment.
Apache Flink responsibilities include savepoint upgrades, related datastream api, clear test coverage and a reliable production handover. Examine the actual tooling and deployment environment.
/ Project scenarios
Repair late-event processing. Define constraints around datastream api, map dependencies and test how the proposed implementation behaves under real operating conditions.
Migrate stateful jobs without data loss. Define constraints around state backends, map dependencies and test how the proposed implementation behaves under real operating conditions.
Reduce checkpoint stalls. Define constraints around watermarks event time, map dependencies and test how the proposed implementation behaves under real operating conditions.
Recover streaming pipelines after failures. Define constraints around exactly-once checkpoints, map dependencies and test how the proposed implementation behaves under real operating conditions.
/ Practical evaluation
A senior engineering interview should surface directly relevant implementation details, debugging history and operational judgment.
Describe a production issue involving DataStream API and what evidence led to a fix.
Which decisions around state backends and watermarks event time were you personally accountable for?
Describe a production issue involving watermarks event time and what evidence led to a fix.
Which decisions around exactly-once checkpoints and Kafka connectors were you personally accountable for?
/ Sourcing process
Define platform versions, deployment constraints, traffic patterns, required integrations and ownership.
Search the active network and partner channels for platform-specific engineering experience.
Discuss real systems, code or configuration decisions, troubleshooting and change control.
Confirm role boundaries, location or remote access, availability, security and interviews.
Profiles, availability and engagement terms are confirmed for each request.
/ Questions
Yes. Tell us the relevant versions, operational environment and the responsibilities connected to DataStream API. We qualify hands-on experience during each search.
These can be included when central to the project. We distinguish practical implementation work from general familiarity and ask about failure scenarios and testing.
We look at production decisions, trade-offs, incident diagnosis, code or infrastructure ownership and the ability to explain decisions without relying on a technology checklist.
Share your architecture, technical constraints, collaboration model and priorities. We can then discuss relevant sourcing channels, evaluation criteria and next steps.
/ Onectus · TEAMS
Tell us the technology, production responsibilities, experience level and working model. We'll activate the appropriate engineering sourcing channels.
