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Flink Jobs in Wisconsin (NOW HIRING)

KOHLS

Senior Data Engineer (Remote)

Menomonee Falls, WI · On-site

$123K - $162K/yr

Implement real time ingestion with Kafka Connect and process streaming data using Spark Streaming, Apache Flink, or similar technologies * Optimize data performance, scalability, and cost efficiency ...

Klarrio Group

WI · On-site

$90 - $120/hr

Hands-on experience with data processing frameworks such as Kafka, Spark, Flink, Storm,... * Hands-on experience with cloud platforms like AWS, Azure, GCP, ... * Affinity with the Agile development ...

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$10

$58

$86

How much do flink jobs pay per hour?

As of Aug 11, 2026, the average hourly pay for flink in Wisconsin is $58.29, according to ZipRecruiter salary data. Most workers in this role earn between $48.99 and $67.93 per hour, depending on experience, location, and employer.

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.

How to start a Flink job?

To start a Flink job, you need to package your application as a JAR file and submit it to a Flink cluster using the command line interface, typically with the 'flink run' command. Ensure your environment is set up with Java and Flink installed, and that your job code is properly configured for the cluster environment. Monitoring and debugging can be done through Flink's web dashboard or logs.

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.

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 is a Flink job?

A Flink job is a program written using Apache Flink, an open-source framework for distributed stream and batch data processing. It involves defining data sources, transformations, and sinks to process large-scale data in real-time or batch mode, often requiring knowledge of Java or Scala and familiarity with Flink's APIs and environment.

What are the key skills and qualifications needed to thrive as an Apache Flink developer?

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 does Flink do?

A Flink job involves developing and maintaining real-time data processing applications using Apache Flink, an open-source stream processing framework. It requires skills in Java or Scala, understanding of distributed systems, and familiarity with data streaming concepts to efficiently process large-scale data in real-time environments.
What are popular job titles related to Flink jobs in Wisconsin? For Flink jobs in Wisconsin, the most frequently searched job titles are:
What job categories do people searching Flink jobs in Wisconsin look for? The top searched job categories for Flink jobs in Wisconsin are:
Flink jobs near you
Infographic showing various Flink job openings in Wisconsin as of August 2026, with employment types broken down into 58% Full Time, and 42% Contract. Highlights an 86% In-person, and 14% Remote job distribution, with an average salary of $121,252 per year, or $58.3 per hour.

Principal Data Engineer

Continuus Technologies LLC

Germantown, WI • On-site

Full-time

Re-posted 2 days ago

Job description

Role OverviewThe Principal Data Engineer is a senior technical authority responsible for defining the organization's data architecture, setting long-term technical strategy, and solving the most complex data engineering challenges. This role influences company-wide data standards, mentors senior engineers, and partners with executive and cross-functional leaders to ensure data platforms scale with the business.Key ResponsibilitiesDefine and evolve the long-term data architecture and technical visionDesign highly scalable, resilient data platforms and pipelinesSet standards for data modeling, reliability, observability, and governanceLead complex, high-risk technical initiatives and migrationsServe as the escalation point for critical data incidents and root cause analysisInfluence tool selection and technology adoption across the data stackMentor Staff and Senior Data Engineers and elevate engineering excellencePartner with leadership to align data strategy with business goalsEnsure data platforms support analytics, ML, and product use cases at scaleQualificationsBachelor's degree in Computer Science, Engineering, or related field (or equivalent experience)10+ years of experience in data engineering or related disciplinesExpert-level SQL and strong proficiency in Python or similar languagesDeep experience with data warehousing, data lakes, and distributed systemsProven track record of designing and operating large-scale data platformsStrong systems thinking and architectural decision-making skillsPreferred ExperienceCloud platforms (AWS, Azure, or GCP)Streaming and real-time systems (Kafka, Spark, Flink, etc.)Advanced data governance, security, and compliance practicesSupporting ML, AI, or product-led data platformsInfluencing technical direction without direct managerial authority