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Flink Jobs in Michigan (NOW HIRING)

Stellantis

Data Engineer

Auburn Hills, MI · On-site

$108K - $130K/yr

Familiarity with time series database, data streaming applications, event driven architectures, Kafka, Flink, and more * Experience with workflow management engines (i.e., Airflow, Luigi, Azure Data ...

Stellantis

Data Engineer

Auburn Hills, MI · On-site

$108K - $130K/yr

Experience with Apache Flink for low-latency stream processing. • Scripting: Proficiency in Python for automation, data analysis, or scripting. • Cloud Platforms: Experience with AWS, Azure, or ...

Stellantis

Data Engineer

Auburn Hills, MI

$108K - $130K/yr

Experience with Apache Flink for low-latency stream processing. * Scripting: Proficiency in Python for automation, data analysis, or scripting. * Cloud Platforms: Experience with AWS, Azure, or GCP ...

HTC Global Services

Senior Data Engineer

Dearborn, MI · On-site

$97K - $132K/yr

Experience with big data technologies such as Apache Spark, Hadoop, Kafka, and Flink. * Experience with cloud platforms including AWS, Azure, or Google Cloud Platform (GCP) and their associated data ...

Stefanini Group

GCP Data Engineer

Dearborn, MI

$105K - $126K/yr

Extensive experience with big data technologies, such as Apache Spark, Hadoop, Kafka, and Flink. * Proven experience with cloud platforms, including AWS, Azure, or GCP, and their data services, such ...

Stefanini

Google Cloud Platform Data Engineer

Dearborn, MI · On-site

$105K - $126K/yr

Extensive experience with big data technologies, such as Apache Spark, Hadoop, Kafka, and Flink.Proven experience with cloud platforms, including AWS, Azure, or Google Cloud Platform, and their data ...

Stefanini Group

GCP Data Engineer

Dearborn, MI · On-site

$61 - $66/hr

Extensive experience with big data technologies, such as Apache Spark, Hadoop, Kafka, and Flink. * Proven experience with cloud platforms, including AWS, Azure, or GCP, and their data services, such ...

Stefanini Group

GCP Data Engineer

Dearborn, MI

$105K - $126K/yr

Extensive experience with big data technologies, such as Apache Spark, Hadoop, Kafka, and Flink. * Proven experience with cloud platforms, including AWS, Azure, or GCP, and their data services, such ...

Stefanini Group

GCP Data Engineer

Dearborn, MI

$105K - $126K/yr

Extensive experience with big data technologies, such as Apache Spark, Hadoop, Kafka, and Flink. * Proven experience with cloud platforms, including AWS, Azure, or GCP, and their data services, such ...

Stefanini

GCP Data Engineer

Dearborn, MI · On-site

$105K - $126K/yr

Extensive experience with big data technologies, such as Apache Spark, Hadoop, Kafka, and Flink. Proven experience with cloud platforms, including AWS, Azure, or GCP, and their data services, such as:

Corning

$104K - $125K/yr

What would be helpful? - Experience with Databricks, Snowflake, Delta Lake, Parquet, Iceberg, PostgreSQL, MySQL, Oracle, or Microsoft SQL Server. - Experience with Kafka, Flink, or other streaming ...

Corning

$104K - $125K/yr

What would be helpful? - Experience with Databricks, Snowflake, Delta Lake, Parquet, Iceberg, PostgreSQL, MySQL, or Microsoft SQL Server.- Experience with Kafka, Flink, or other real-time and ...

FastTek

Software Engineer

Dearborn, MI

Extensive experience with big data technologies (e.g., Apache Spark, Hadoop, Kafka, Flink). * Proven experience with cloud platforms (AWS, Azure, GCP) and their data services (e.g., AWS Glue, S3 ...

Corning

$104K - $125K/yr

... Flink, or other streaming technologies. - Experience with time-series data, sensor data, industrial IoT, or operational technology data.- Familiarity with Airflow, Dagster, Prefect, PI Integrator ...

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$8

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$74

How much do flink jobs pay per hour?

As of Aug 6, 2026, the average hourly pay for flink in Michigan is $50.34, according to ZipRecruiter salary data. Most workers in this role earn between $42.31 and $58.65 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 Michigan? For Flink jobs in Michigan, the most frequently searched job titles are:
What job categories do people searching Flink jobs in Michigan look for? The top searched job categories for Flink jobs in Michigan are:
Flink jobs near you
Infographic showing various Flink job openings in Michigan as of August 2026, with employment types broken down into 57% Full Time, and 43% Contract. Highlights an 86% In-person, and 14% Remote job distribution, with an average salary of $104,703 per year, or $50.3 per hour.

Data Engineer

Stellantis

Auburn Hills, MI • On-site

$108K - $130K/yr

Full-time

Re-posted 4 days ago

Stellantis rating

7.5

Company rating: 7.5 out of 10

Based on 130 frontline employees who took The Breakroom Quiz

14th of 44 rated automakers

Job description

The AI & Data Analytics Team is looking for a Senior Data Engineer to join our team. In this role, you will be responsible for designing, building, and optimizing robust data pipelines that process massive datasets in both batch and real-time. You will work at the intersection of software engineering and data science, ensuring that our data architecture is scalable, reliable, and follows industry best practices.
Priorities can change in a fast-paced environment like ours, so this role includes, but is not limited to, the following responsibilities:
  • Pipeline Development: Design and implement complex data processing pipelines using Apache Spark.
  • Architectural Leadership: Build scalable, distributed systems that handle high-throughput data streams and large-scale batch processing.
  • Infrastructure as Code: Manage and provision cloud infrastructure using Terraform.
  • CI/CD & Automation: Streamline development workflows by implementing and maintaining GitHub Actions for automated testing and deployment.
  • Code Quality: Uphold rigorous software engineering standards, including comprehensive unit/integration testing, code reviews, and maintainable documentation.
  • Collaboration: Work closely with stakeholders to translate business requirements into technical specifications.

Basic Qualifications:
  • Bachelors degree in Computer Science, Engineering, Mathematics, or a related technical discipline
  • A minimum of 5 years of experience in the data engineering and software development life cycle. Including:
    • A minimum of 4 years of hands-on experience in building and maintaining production data applications, current experience in both relational and columnar data stores.
    • A minimum of 4 years of hands-on experience working with AWS cloud services
  • Comprehensive experience with one or more programming languages such as Python, Java, or Rust
  • Comprehensive experience working with Big Data platforms (i.e., Spark, Google Big Query, Azure, AWS S3, etc.)
  • Familiarity with time series database, data streaming applications, event driven architectures, Kafka, Flink, and more
  • Experience with workflow management engines (i.e., Airflow, Luigi, Azure Data Factory, etc.)
  • Experience with designing and implementing real-time pipelines
  • Experience with data quality and validation
  • Experience with API design
  • Distributed Computing: Deep expertise in Apache Spark (Core, SQL, and Structured Streaming).
  • Programming Mastery: Strong proficiency in Scala or Java. You should be comfortable building production-grade applications in a JVM-based environment.
  • SQL Proficiency: Advanced knowledge of SQL for data transformation, analysis, and performance tuning.
  • DevOps & Tools: Hands-on experience with Terraform for infrastructure management and GitHub Actions for CI/CD pipelines.
  • Software Engineering Foundation: Solid understanding of data structures, algorithms, and design patterns. Experience applying "Clean Code" principles to data engineering.
  • Stream Processing: Experience with Apache Flink for low-latency stream processing.
  • Scripting: Proficiency in Python for automation, data analysis, or scripting.
  • Cloud Platforms: Experience with AWS, Azure, or GCP data services (e.g., EMR, Glue, Databricks).
  • Data Modeling: Familiarity with dimensional modeling, Lakehouse architectures (Delta Lake, Iceberg), or NoSQL databases.

Preferred Qualifications:
  • Comprehensive knowledge of relational database concepts, including data architecture, operational data stores, Interface processes, multidimensional modeling, master data management, and data manipulation
  • Expert knowledge and experience with custom ETL design, implementation and maintenance
  • Comprehensive experience designing, implementing, and iterating data pipelines using Big Data technologies
  • Certification in AWS or other cloud providers
  • Experience with Databricks notebook workflows
  • Experience with Terraform

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