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Data Engineer Airflow Jobs in Milwaukee, WI (NOW HIRING)

Techvilla Solutions

ML Ops Engineer

Greendale, WI · On-site

Collaborate with Data Scientists, ML Engineers, Data Engineers, and DevOps teams. * Troubleshoot ... Experience with Apache Airflow, Databricks, Spark, or Kafka. * Knowledge of LLMOps/GenAI deployment ...

Techvilla Solutions

ML Ops Engineer

Hartland, WI · On-site

Collaborate with Data Scientists, ML Engineers, Data Engineers, and DevOps teams. * Troubleshoot ... Experience with Apache Airflow, Databricks, Spark, or Kafka. * Knowledge of LLMOps/GenAI deployment ...

Techvilla Solutions

ML Ops Engineer

Muskego, WI · On-site

Collaborate with Data Scientists, ML Engineers, Data Engineers, and DevOps teams. * Troubleshoot ... Experience with Apache Airflow, Databricks, Spark, or Kafka. * Knowledge of LLMOps/GenAI deployment ...

Techvilla Solutions

ML Ops Engineer

New Berlin, WI · On-site

Collaborate with Data Scientists, ML Engineers, Data Engineers, and DevOps teams. * Troubleshoot ... Experience with Apache Airflow, Databricks, Spark, or Kafka. * Knowledge of LLMOps/GenAI deployment ...

Techvilla Solutions

ML Ops Engineer

Richfield, WI · On-site

Collaborate with Data Scientists, ML Engineers, Data Engineers, and DevOps teams. * Troubleshoot ... Experience with Apache Airflow, Databricks, Spark, or Kafka. * Knowledge of LLMOps/GenAI deployment ...

Techvilla Solutions

ML Ops Engineer

Brookfield, WI · On-site

Collaborate with Data Scientists, ML Engineers, Data Engineers, and DevOps teams. * Troubleshoot ... Experience with Apache Airflow, Databricks, Spark, or Kafka. * Knowledge of LLMOps/GenAI deployment ...

Techvilla Solutions

ML Ops Engineer

Wauwatosa, WI · On-site

Collaborate with Data Scientists, ML Engineers, Data Engineers, and DevOps teams. * Troubleshoot ... Experience with Apache Airflow, Databricks, Spark, or Kafka. * Knowledge of LLMOps/GenAI deployment ...

Techvilla Solutions

ML Ops Engineer

Vernon, WI · On-site

Collaborate with Data Scientists, ML Engineers, Data Engineers, and DevOps teams. * Troubleshoot ... Experience with Apache Airflow, Databricks, Spark, or Kafka. * Knowledge of LLMOps/GenAI deployment ...

Techvilla Solutions

ML Ops Engineer

Saint Francis, WI

Collaborate with Data Scientists, ML Engineers, Data Engineers, and DevOps teams. * Troubleshoot ... Experience with Apache Airflow, Databricks, Spark, or Kafka. * Knowledge of LLMOps/GenAI deployment ...

Techvilla Solutions

ML Ops Engineer

Delafield, WI · On-site

Collaborate with Data Scientists, ML Engineers, Data Engineers, and DevOps teams. * Troubleshoot ... Experience with Apache Airflow, Databricks, Spark, or Kafka. * Knowledge of LLMOps/GenAI deployment ...

Techvilla Solutions

ML Ops Engineer

Sussex, WI · On-site

Collaborate with Data Scientists, ML Engineers, Data Engineers, and DevOps teams. * Troubleshoot ... Experience with Apache Airflow, Databricks, Spark, or Kafka. * Knowledge of LLMOps/GenAI deployment ...

Techvilla Solutions

ML Ops Engineer

Brown Deer, WI

Collaborate with Data Scientists, ML Engineers, Data Engineers, and DevOps teams. * Troubleshoot ... Experience with Apache Airflow, Databricks, Spark, or Kafka. * Knowledge of LLMOps/GenAI deployment ...

Techvilla Solutions

ML Ops Engineer

Nashotah, WI

Collaborate with Data Scientists, ML Engineers, Data Engineers, and DevOps teams. * Troubleshoot ... Experience with Apache Airflow, Databricks, Spark, or Kafka. * Knowledge of LLMOps/GenAI deployment ...

Techvilla Solutions

ML Ops Engineer

North Lake, WI

Collaborate with Data Scientists, ML Engineers, Data Engineers, and DevOps teams. * Troubleshoot ... Experience with Apache Airflow, Databricks, Spark, or Kafka. * Knowledge of LLMOps/GenAI deployment ...

Techvilla Solutions

ML Ops Engineer

Hubertus, WI

Collaborate with Data Scientists, ML Engineers, Data Engineers, and DevOps teams. * Troubleshoot ... Experience with Apache Airflow, Databricks, Spark, or Kafka. * Knowledge of LLMOps/GenAI deployment ...

Techvilla Solutions

ML Ops Engineer

Colgate, WI

Collaborate with Data Scientists, ML Engineers, Data Engineers, and DevOps teams. * Troubleshoot ... Experience with Apache Airflow, Databricks, Spark, or Kafka. * Knowledge of LLMOps/GenAI deployment ...

Techvilla Solutions

ML Ops Engineer

River Hills, WI

Collaborate with Data Scientists, ML Engineers, Data Engineers, and DevOps teams. * Troubleshoot ... Experience with Apache Airflow, Databricks, Spark, or Kafka. * Knowledge of LLMOps/GenAI deployment ...

Techvilla Solutions

ML Ops Engineer

Cudahy, WI · On-site

Collaborate with Data Scientists, ML Engineers, Data Engineers, and DevOps teams. * Troubleshoot ... Experience with Apache Airflow, Databricks, Spark, or Kafka. * Knowledge of LLMOps/GenAI deployment ...

Techvilla Solutions

ML Ops Engineer

Glendale, WI · On-site

Collaborate with Data Scientists, ML Engineers, Data Engineers, and DevOps teams. * Troubleshoot ... Experience with Apache Airflow, Databricks, Spark, or Kafka. * Knowledge of LLMOps/GenAI deployment ...

Techvilla Solutions

ML Ops Engineer

Bayside, WI

Collaborate with Data Scientists, ML Engineers, Data Engineers, and DevOps teams. * Troubleshoot ... Experience with Apache Airflow, Databricks, Spark, or Kafka. * Knowledge of LLMOps/GenAI deployment ...

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Showing results 21-40

All JobsData Engineer Airflow JobsData Engineer Airflow Jobs in Milwaukee, WI

Data Engineer Airflow information

See Milwaukee, WI salary details

$43.8K

$127.8K

$174.9K

How much do data engineer airflow jobs pay per year?

As of Sep 6, 2026, the average yearly pay for data engineer airflow in Milwaukee, WI is $127,802.00, according to ZipRecruiter salary data. Most workers in this role earn between $112,800.00 and $135,500.00 per year, depending on experience, location, and employer.

What does a data engineer specializing in Airflow do?

A Data Engineer specializing in Airflow is responsible for designing, building, and maintaining data pipelines using Apache Airflow, an open-source workflow orchestration tool. Their main job is to automate, schedule, and monitor complex data workflows, ensuring data moves reliably between systems and is processed efficiently. They often collaborate with data scientists, analysts, and other engineers to make sure that data is accessible, accurate, and up to date for business needs. Expertise in Airflow helps streamline data operations, optimize performance, and improve data pipeline reliability.

How does a data engineer specializing in Airflow typically collaborate with data scientists and analysts?

Data Engineers working with Airflow play a crucial role in enabling data scientists and analysts to access reliable, up-to-date data. They design and maintain ETL pipelines that automate data movement and transformation, ensuring data is clean and available for analysis. Collaboration often involves gathering requirements, troubleshooting pipeline issues, and optimizing data workflows to meet the needs of downstream users. Effective communication and documentation are essential, as data engineers must align technical solutions with the analytical goals of the broader team.

What are the key skills and qualifications needed to thrive as a data engineer specializing in Airflow, and why are they important?

To thrive as a Data Engineer with an Airflow focus, you need strong programming skills in Python, expertise in data pipeline design, and experience with distributed systems, often supported by a degree in computer science or a related field. Familiarity with Apache Airflow, cloud platforms (like AWS or GCP), and database technologies, as well as certifications in cloud data engineering, are typically required. Outstanding problem-solving, attention to detail, and effective communication help you collaborate on complex data workflows and troubleshoot issues efficiently. These skills ensure robust, scalable, and reliable data infrastructure, enabling organizations to make data-driven decisions with confidence.

What is the difference between Data Engineer Airflow vs Data Engineer?

AspectData Engineer AirflowData Engineer
Primary FocusWorkflow orchestration and pipeline automation using AirflowData collection, storage, transformation, and pipeline development
Required SkillsPython, Airflow, ETL processes, cloud platformsSQL, Python, ETL, data modeling, cloud services
Work EnvironmentData teams, cloud environments, automation pipelinesData warehouses, big data platforms, cloud infrastructure
CertificationsAirflow certifications, Python, cloud certificationsSQL, cloud certifications, data engineering certifications

While both roles involve data pipeline work, Data Engineer Airflow specializes in designing and managing workflows with Airflow, focusing on automation and orchestration. In contrast, Data Engineer has a broader scope, including data storage, transformation, and pipeline development across various tools and platforms.

What are popular job titles related to Data Engineer Airflow jobs in Milwaukee, WI?

For Data Engineer Airflow jobs in Milwaukee, WI, the most frequently searched job titles are:

What job categories do people searching Data Engineer Airflow jobs in Milwaukee, WI look for?

The top searched job categories for Data Engineer Airflow jobs in Milwaukee, WI are:

What cities near Milwaukee, WI are hiring for Data Engineer Airflow jobs?

Cities near Milwaukee, WI with the most Data Engineer Airflow job openings:

Data Engineer Airflow jobs near you
Infographic showing various Data Engineer Airflow job openings in Milwaukee, WI as of August 2026, with employment types broken down into 1% As Needed, 82% Full Time, 14% Part Time, and 3% Contract. Highlights an 86% Physical, 4% Hybrid, and 10% Remote job distribution, with an average salary of $127,802 per year, or $61.4 per hour.

ML Ops Engineer

Techvilla Solutions

Greendale, WI • On-site

Full-time

Posted 17 days ago

Job description

We are looking for an experienced ML Ops Engineer to build, automate, and maintain scalable machine learning infrastructure and deployment pipelines. The ideal candidate will have strong experience with cloud platforms, CI/CD, containerization, model deployment, monitoring, and ML lifecycle management.

Roles and Responsibilities
  • Build and maintain MLOps pipelines for model development, deployment, monitoring, and retraining.
  • Automate ML workflows using CI/CD, infrastructure as code, and workflow orchestration.
  • Deploy and manage machine learning models across cloud and on-premise environments.
  • Implement model versioning, experiment tracking, feature management, and model governance.
  • Build scalable infrastructure using Docker, Kubernetes, and cloud services.
  • Monitor model performance, data quality, system health, and production workloads.
  • Collaborate with Data Scientists, ML Engineers, Data Engineers, and DevOps teams.
  • Troubleshoot production ML systems and optimize reliability, scalability, and performance.
  • Implement security, access controls, logging, and compliance best practices.
Required Skills
  • 5+ years of experience in DevOps, ML Engineering, MLOps, or a related field.
  • Strong experience with MLOps concepts and ML lifecycle management.
  • Hands-on experience with Python and scripting.
  • Experience with AWS, Azure, or GCP.
  • Strong knowledge of Docker and Kubernetes.
  • Experience with CI/CD tools such as Jenkins, GitHub Actions, GitLab CI, or Azure DevOps.
  • Experience with MLflow, Kubeflow, SageMaker, Vertex AI, Azure ML, or similar ML platforms.
  • Experience with Git, Terraform, and infrastructure automation.
  • Knowledge of model monitoring, observability, data validation, and model performance tracking.
  • Strong understanding of REST APIs, microservices, Linux, and cloud-native architectures.
Preferred Skills
  • Experience with Apache Airflow, Databricks, Spark, or Kafka.
  • Knowledge of LLMOps/GenAI deployment and monitoring.
  • Experience with model serving frameworks such as KServe, Seldon, or NVIDIA Triton.
  • Familiarity with Prometheus, Grafana, ELK, or similar observability tools.
  • Understanding of ML security, governance, and responsible AI practices.
Education

Bachelor’s degree in Computer Science, Engineering, Data Science, or a related technical field, or equivalent practical experience.

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