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Flink Jobs (NOW HIRING)

Flink Manager

$54 - $74/hr

United States JobType: full-time As a Flink Manager, you will be responsible for driving real-time streaming initiatives, managing high-performing engineering teams, and architecting scalable data ...

As a Flink Leader, you will play a critical role in architecting next-generation streaming platforms and enabling real-time analytics capabilities for enterprise-scale applications. You will mentor ...

Java Flink with Datastream API

Dallas, TX · On-site

$50.50 - $65.25/hr

Job Title Flink with Datastream API Location Dallas, TX, partial remote role Requirements for Resource: * Proficient in writing and supporting both functional and non-functional aspects of Flink with ...

Job#: 3031027 Flink Engineer Location: Remote Employment Type: Contract Role Overview We are seeking a Flink Engineer to support a growing streaming data platform. This role involves extending an ...

You will be working in a team with other known Flink experts iterating on an already existing implementation based on actual usage data and product requirements. With the team you will also be ...

Java Apache Flink Developer

Reston, VA · On-site

$53 - $68.75/hr

Company Description Big Data applications on the Flink Platform using Java Thanks Regarding Kaspa Sudarshan Phone: 404-496-4368*407 Direct: 404-496-4927 Qualifications Additional Information All your ...

Java Apache Flink Developer

Reston, VA · On-site

$53 - $68.75/hr

Big Data applications on the Flink Platform using Java Thanks Regarding Kaspa Sudarshan Phone: 404-496-4368*407 Direct: 404-496-4927 Additional Information All your information will be kept ...

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How much do flink jobs pay per hour?

As of May 31, 2026, the average hourly pay for flink in the United States is $57.75, according to ZipRecruiter salary data. Most workers in this role earn between $48.56 and $67.31 per hour, depending on experience, location, and employer.

What are the key skills and qualifications needed to thrive as an Apache Flink Developer, and why are they important?

To thrive as an Apache Flink Developer, you need strong programming skills (typically in Java or Scala), a solid understanding of distributed systems, and experience with real-time data processing frameworks, preferably backed by a relevant degree in computer science or engineering. Familiarity with Flink’s APIs, stream processing concepts, and integration with tools like Kafka, Hadoop, or AWS, as well as certifications in big data technologies, are highly valuable. Analytical thinking, problem-solving abilities, and effective communication are essential soft skills for collaborating with teams and troubleshooting complex data workflows. These skills are crucial for building scalable, reliable, and efficient data pipelines that drive real-time analytics and business decisions.

What are some common challenges faced by Apache Flink developers and how can they be overcome?

Apache Flink developers often encounter challenges such as handling stateful stream processing at scale, ensuring low-latency data flows, and managing the complexities of distributed systems. Addressing these issues typically involves careful job design, leveraging Flink's checkpointing and state management features, and optimizing resource allocation. Collaborating closely with DevOps and data engineering teams can also help in troubleshooting deployment and performance bottlenecks, ensuring smooth operation in production environments.

What are Flink jobs?

Flink jobs are user-defined programs that run on Apache Flink, an open-source stream processing framework. These jobs process data in real-time or in batches, allowing organizations to analyze, transform, or aggregate large volumes of data efficiently. Flink jobs are written in languages like Java, Scala, or Python and can be used for a variety of applications such as event-driven analytics, real-time monitoring, and data pipeline processing. They can be deployed on clusters to handle large-scale data processing with low latency and high throughput.

What is the difference between Flink vs Kafka Streams?

AspectFlinkKafka Streams
Primary UseDistributed stream processing framework for large-scale data processingClient library for real-time stream processing within Kafka
Deployment EnvironmentCluster-based, supports standalone and cloud deploymentsEmbedded within Java applications, runs on client machines
ComplexityRequires setup of cluster and infrastructureSimpler to integrate with existing Kafka setup
Use CasesComplex event processing, large-scale analyticsReal-time data transformation, lightweight processing

Flink and Kafka Streams are both popular stream processing tools, but Flink is suited for large-scale, complex processing across clusters, while Kafka Streams is ideal for lightweight, real-time processing within Kafka environments. Your choice depends on processing complexity and deployment needs.

More about Flink jobs
What cities are hiring for Flink jobs? Cities with the most Flink job openings:
What states have the most Flink jobs? States with the most job openings for Flink jobs include:
What job categories do people searching Flink jobs look for? The top searched job categories for Flink jobs are:
Infographic showing various Flink job openings in the United States as of May 2026, with employment types broken down into 17% Full Time, and 83% Contract. Highlights an 67% In-person, and 33% Remote job distribution, with an average salary of $120,128 per year, or $57.8 per hour.

$54 - $74/hr

Full-time

Posted 3 days ago


Job description

This role is for one of the Weekday's clientsa
Salary range: Rs 10000000 - Rs 40000000 (ie INR 100 - 400 LPA)Min Experience: 8 years
Location: United States
JobType: full-time
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
Key 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.
Required Qualifications
  • 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.
Preferred Qualifications
  • 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.
Leadership Expectations
The ideal candidate is a strategic thinker and technical leader who can balance hands-on involvement with managerial responsibilities. You will champion best practices in Flink architecture, ensure production stability, and drive continuous improvement across streaming platforms.