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Job Description & How to Apply Below
Senior Software Engineer – Java / Apache Flink (Hybrid)
Location:
Toronto, ON (Hybrid – 3 days in-office / 2 days remote)
Position Overview
We 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 Data Stream 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 serialize rs, and manage RocksDB State Backend performance.
Fault Tolerance & Reliability: Implement and manage robust state management strategies, including checkpointing, save points, and schema evolution rules to ensure exactly-once processing guarantees.
Cross-functional Collaboration:
Partner with Data Science, Dev Ops, and Product teams to translate complex business analytics into highly performant real-time metrics.
Required
Skills & Qualifications
Experience:
5+ years of professional 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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