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Data Engineer Flink Jobs in Michigan (NOW HIRING)

Stellantis

Data Engineer

Auburn Hills, MI · On-site

$108K - $130K/yr

The AI & Data Analytics Team is looking for a Senior Data Engineer to join our team. In this role ... Experience with Apache Flink for low-latency stream processing. * Scripting: Proficiency in Python ...

Stellantis

Data Engineer

Auburn Hills, MI · On-site

$108K - $130K/yr

Stellantis is looking for a Senior Data Engineer to join their AI & Data Analytics Team. In this ... Experience with Apache Flink for low-latency stream processing. • Scripting: Proficiency in ...

Stellantis

Data Engineer

Auburn Hills, MI

$108K - $130K/yr

The AI & Data Analytics Team is looking for a Senior Data Engineer to join our team. In this role ... Experience with Apache Flink for low-latency stream processing. * Scripting: Proficiency in Python ...

Corning

$104K - $125K/yr

... Kafka, Flink, or other streaming technologies. - Experience with time-series data, sensor data ... Data Engineering, technical subject-matter expertise, AI/ML, or future technical leadership ...

Corning

$104K - $125K/yr

... with Kafka, Flink, or other streaming and near-real-time data technologies. - Experience with ... engineering practices. - Experience with industrial IoT, operational technology systems, PI ...

Corning

$104K - $125K/yr

... Flink, or other real-time and streaming technologies.- Experience with Airflow, Dagster, Prefect ... Data Engineering projects with direct impact on manufacturing and business operations.- Exposure to ...

Corning

$104K - $125K/yr

... Flink, or other real-time and streaming technologies.- Experience with Airflow, Dagster, Prefect ... Data Engineering projects with direct impact on manufacturing and business operations.- Exposure to ...

All JobsData Engineer Flink JobsData Engineer Flink Jobs in Michigan

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, and why are they important?

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 job categories do people searching Data Engineer Flink jobs in Michigan look for? The top searched job categories for Data Engineer Flink jobs in Michigan are:
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Data Engineer Flink jobs near you
Data Engineer

Data Engineer

Stellantis

Auburn Hills, MI • On-site

$108K - $130K/yr

Full-time

Re-posted 17 days ago

Stellantis rating

7.5

Company rating: 7.5 out of 10

Based on 128 frontline employees who took The Breakroom Quiz

15th 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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