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Data Engineer Flink Jobs in Wisconsin (NOW HIRING)

Senior Data Engineer (Remote)

Menomonee Falls, WI · On-site

$123K - $162K/yr

About the Role As Senior Software Engineer, you will collaborate closely with design, product and ... using Spark Streaming, Apache Flink, or similar technologies * Optimize data performance ...

WI · On-site

$90 - $120/hr

... world of data engineering? Do you want to join a fast-growing international company with big ... Hands-on experience with data processing frameworks such as Kafka, Spark, Flink, Storm,... * Hands ...

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Data Engineer Flink information

What are some common challenges data engineers face when working with Apache Flink in a production environment?

Data Engineers working with Apache Flink often encounter challenges such as managing stateful stream processing at scale, ensuring fault tolerance, and optimizing resource usage for real-time data pipelines. Handling late-arriving data and tuning Flink jobs for low latency and high throughput are also frequent hurdles. Collaborating closely with data scientists and application developers is key to aligning data models and ensuring smooth data flow throughout the system.

What are the key skills and qualifications needed to thrive as a data engineer Flink?

To thrive as a Data Engineer specializing in Flink, you need strong programming skills (especially in Java or Scala), a solid understanding of distributed data processing, and experience with data architecture. Familiarity with Apache Flink, stream processing frameworks, big data tools (like Kafka, Hadoop, or Spark), and cloud platforms is typically required, along with relevant certifications. Excellent problem-solving abilities, attention to detail, and effective teamwork and communication skills help you excel in complex data environments. These competencies are crucial for building reliable, scalable data pipelines that power real-time analytics and business decision-making.

What is a data engineer Flink?

A Data Engineer Flink is a data engineering professional who specializes in using Apache Flink, an open-source stream processing framework, to build, maintain, and optimize systems that process large-scale data in real time. They design and implement data pipelines, ensure data quality and consistency, and collaborate with other engineering teams to deliver reliable and scalable data solutions. Their expertise allows organizations to process, analyze, and react to data as it is generated, enabling real-time insights and decision-making.
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What cities in Wisconsin are hiring for Data Engineer Flink jobs? Cities in Wisconsin with the most Data Engineer Flink job openings:
Infographic showing various Data Engineer Flink job openings in Wisconsin as of August 2026, with employment types broken down into 1% As Needed, 82% Full Time, 13% Part Time, and 4% Contract. Highlights an 87% Physical, 3% Hybrid, and 10% Remote job distribution.

Principal Data Engineer

Continuus Technologies LLC

Germantown, WI • On-site

Full-time

Re-posted 3 hours 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