Job Title: Senior Software Engineer – Java / Apache Flink (Hybrid)
Location: Toronto, ON (Hybrid – 3 days in-office / 2 days remote)
Position OverviewWe are seeking a talented
Senior Java Engineer
with deep expertise in
Apache Flink
to join our growing Core Data Platform team in Toronto.
In this role, you will design, build, and optimize high-throughput, low-latency distributed streaming pipelines. You will play a critical part in evolving our real-time data architecture, transitioning legacy batch workflows into highly scalable, event-driven streaming solutions. This is a
hybrid role
requiring three days a week in our downtown Toronto office, offering a perfect balance of collaborative in-person whiteboarding and remote flexibility.
Core Responsibilities
Pipeline Engineering:
Design, develop, and maintain production-grade, stateful stream processing applications using the
Java DataStream and Table/SQL APIs
in Apache Flink.
Architecture Evolution:
Architect real-time event-driven systems utilizing
Apache Kafka
or AWS Kinesis integrated seamlessly with Flink.
Performance Tuning:
Optimize Flink cluster configurations, manage memory tuning (Managed vs. Unmanaged memory), write custom serializers, and manage
RocksDB State Backend
performance.
Fault Tolerance & Reliability:
Implement and manage robust state management strategies, including checkpointing, savepoints,



and schema evolution rules to ensure exactly-once processing guarantees.
Cross-functional Collaboration:
Partner with Data Science, DevOps, and Product teams to translate complex business analytics into highly performant real-time metrics.
Required Skills & Qualifications
Experience:
5+ years of skilled software engineering experience in backend development, with a minimum of 2+ years of hands-on experience building production pipelines with
Apache Flink .
Java Expertise:
Mastery of core
Java (Java 11/17+), including concurrency packages, multithreading, garbage collection tuning, and memory management.
Distributed Ecosystems:
Strong experience with event streaming backbones (specifically
Apache Kafka, schema registries, and consumer/producer APIs).
Data Fundamentals:
Deep understanding of stream processing concepts such as event-time processing, watermarking, late data handling, and tumbling/sliding windows.
CI/CD & Cloud:
Familiarity deploying Flink applications into containerized cloud environments ( Kubernetes, AWS, or Managed Flink providers like Ververica/Confluent Cloud).
Location Constraint:
Must be currently living in or willing to relocate to the
Greater Toronto Area (GTA)
and able to commute to our downtown office 3 days a week.
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