Flink Manager

Weekday AI

51d•$10,000,000 - $40,000,000

About The Position

As a Flink Manager, you will be responsible for driving real-time streaming initiatives, managing high-performing engineering teams, and architecting scalable data solutions that power mission-critical business applications. You will collaborate closely with product, analytics, infrastructure, and leadership teams to translate business requirements into resilient streaming architectures.

Requirements

8–12 years of overall experience in data engineering, distributed systems, or backend engineering.
Strong hands-on expertise in Apache Flink (minimum 3–5 years preferred).
Deep understanding of stream processing concepts including event-time semantics, watermarking, state backends, and exactly-once guarantees.
Proven experience designing and managing high-throughput, low-latency Flink pipelines.
Strong programming skills in Java or Scala for Flink development.
Experience with distributed messaging systems (e.g., Kafka) and data storage systems.
Familiarity with cluster resource management frameworks (YARN, Kubernetes, or similar).
Strong debugging, troubleshooting, and performance tuning skills specific to Flink workloads.
Experience leading engineering teams and managing cross-functional stakeholders.

Nice To Haves

Experience deploying Flink in cloud environments (AWS, Azure, or GCP).
Knowledge of batch and stream unification architectures.
Exposure to big data ecosystems including Hadoop or Spark.
Understanding of CI/CD practices for streaming applications.
Experience implementing real-time analytics, fraud detection, personalization, or IoT streaming use cases.

Responsibilities

Lead the design, development, and deployment of real-time data processing pipelines using Apache Flink.
Architect scalable, fault-tolerant, and low-latency streaming systems leveraging Flink’s DataStream and Table APIs.
Manage end-to-end lifecycle of Flink applications including development, testing, optimization, monitoring, and production support.
Drive best practices for state management, checkpointing, windowing, event-time processing, and fault tolerance in Flink.
Optimize Flink job performance, resource allocation, and cluster tuning for high-throughput environments.
Oversee integration of Flink with distributed systems such as Kafka, data lakes, warehouses, and microservices.
Lead and mentor a team of data engineers, conducting code reviews and enforcing engineering excellence standards.
Collaborate with DevOps teams to manage Flink deployments on cloud and on-prem environments.
Establish monitoring, logging, and alerting mechanisms for streaming pipelines to ensure high availability and reliability.
Contribute to roadmap planning for streaming and real-time analytics platforms.