We are looking for an experienced ML Ops Engineer to build, automate, and maintain scalable machine ... Experience with Apache Airflow, Databricks, Spark, or Kafka. * Knowledge of LLMOps/GenAI deployment ...
We are looking for an experienced ML Ops Engineer to build, automate, and maintain scalable machine ... Experience with Apache Airflow, Databricks, Spark, or Kafka. * Knowledge of LLMOps/GenAI deployment ...
We are looking for an experienced ML Ops Engineer to build, automate, and maintain scalable machine ... Experience with Apache Airflow, Databricks, Spark, or Kafka. * Knowledge of LLMOps/GenAI deployment ...
We are looking for an experienced ML Ops Engineer to build, automate, and maintain scalable machine ... Experience with Apache Airflow, Databricks, Spark, or Kafka. * Knowledge of LLMOps/GenAI deployment ...
We are looking for an experienced ML Ops Engineer to build, automate, and maintain scalable machine ... Experience with Apache Airflow, Databricks, Spark, or Kafka. * Knowledge of LLMOps/GenAI deployment ...
We are looking for an experienced ML Ops Engineer to build, automate, and maintain scalable machine ... Experience with Apache Airflow, Databricks, Spark, or Kafka. * Knowledge of LLMOps/GenAI deployment ...
We are looking for an experienced ML Ops Engineer to build, automate, and maintain scalable machine ... Experience with Apache Airflow, Databricks, Spark, or Kafka. * Knowledge of LLMOps/GenAI deployment ...
We are looking for an experienced ML Ops Engineer to build, automate, and maintain scalable machine ... Experience with Apache Airflow, Databricks, Spark, or Kafka. * Knowledge of LLMOps/GenAI deployment ...
We are looking for an experienced ML Ops Engineer to build, automate, and maintain scalable machine ... Experience with Apache Airflow, Databricks, Spark, or Kafka. * Knowledge of LLMOps/GenAI deployment ...
We are looking for an experienced ML Ops Engineer to build, automate, and maintain scalable machine ... Experience with Apache Airflow, Databricks, Spark, or Kafka. * Knowledge of LLMOps/GenAI deployment ...
We are looking for an experienced ML Ops Engineer to build, automate, and maintain scalable machine ... Experience with Apache Airflow, Databricks, Spark, or Kafka. * Knowledge of LLMOps/GenAI deployment ...
We are looking for an experienced ML Ops Engineer to build, automate, and maintain scalable machine ... Experience with Apache Airflow, Databricks, Spark, or Kafka. * Knowledge of LLMOps/GenAI deployment ...
We are looking for an experienced ML Ops Engineer to build, automate, and maintain scalable machine ... Experience with Apache Airflow, Databricks, Spark, or Kafka. * Knowledge of LLMOps/GenAI deployment ...
We are looking for an experienced ML Ops Engineer to build, automate, and maintain scalable machine ... Experience with Apache Airflow, Databricks, Spark, or Kafka. * Knowledge of LLMOps/GenAI deployment ...
We are looking for an experienced ML Ops Engineer to build, automate, and maintain scalable machine ... Experience with Apache Airflow, Databricks, Spark, or Kafka. * Knowledge of LLMOps/GenAI deployment ...
We are looking for an experienced ML Ops Engineer to build, automate, and maintain scalable machine ... Experience with Apache Airflow, Databricks, Spark, or Kafka. * Knowledge of LLMOps/GenAI deployment ...
We are looking for an experienced ML Ops Engineer to build, automate, and maintain scalable machine ... Experience with Apache Airflow, Databricks, Spark, or Kafka. * Knowledge of LLMOps/GenAI deployment ...
We are looking for an experienced ML Ops Engineer to build, automate, and maintain scalable machine ... Experience with Apache Airflow, Databricks, Spark, or Kafka. * Knowledge of LLMOps/GenAI deployment ...
We are looking for an experienced ML Ops Engineer to build, automate, and maintain scalable machine ... Experience with Apache Airflow, Databricks, Spark, or Kafka. * Knowledge of LLMOps/GenAI deployment ...
We are looking for an experienced ML Ops Engineer to build, automate, and maintain scalable machine ... Experience with Apache Airflow, Databricks, Spark, or Kafka. * Knowledge of LLMOps/GenAI deployment ...
We are looking for an experienced ML Ops Engineer to build, automate, and maintain scalable machine ... Experience with Apache Airflow, Databricks, Spark, or Kafka. * Knowledge of LLMOps/GenAI deployment ...
We are looking for an experienced ML Ops Engineer to build, automate, and maintain scalable machine ... Experience with Apache Airflow, Databricks, Spark, or Kafka. * Knowledge of LLMOps/GenAI deployment ...
We are looking for an experienced ML Ops Engineer to build, automate, and maintain scalable machine ... Experience with Apache Airflow, Databricks, Spark, or Kafka. * Knowledge of LLMOps/GenAI deployment ...
We are looking for an experienced ML Ops Engineer to build, automate, and maintain scalable machine ... Experience with Apache Airflow, Databricks, Spark, or Kafka. * Knowledge of LLMOps/GenAI deployment ...
We are looking for an experienced ML Ops Engineer to build, automate, and maintain scalable machine ... Experience with Apache Airflow, Databricks, Spark, or Kafka. * Knowledge of LLMOps/GenAI deployment ...
We are looking for an experienced ML Ops Engineer to build, automate, and maintain scalable machine ... Experience with Apache Airflow, Databricks, Spark, or Kafka. * Knowledge of LLMOps/GenAI deployment ...
We are looking for an experienced ML Ops Engineer to build, automate, and maintain scalable machine ... Experience with Apache Airflow, Databricks, Spark, or Kafka. * Knowledge of LLMOps/GenAI deployment ...
We are looking for an experienced ML Ops Engineer to build, automate, and maintain scalable machine ... Experience with Apache Airflow, Databricks, Spark, or Kafka. * Knowledge of LLMOps/GenAI deployment ...
We are looking for an experienced ML Ops Engineer to build, automate, and maintain scalable machine ... Experience with Apache Airflow, Databricks, Spark, or Kafka. * Knowledge of LLMOps/GenAI deployment ...
We are looking for an experienced ML Ops Engineer to build, automate, and maintain scalable machine ... Experience with Apache Airflow, Databricks, Spark, or Kafka. * Knowledge of LLMOps/GenAI deployment ...
We are looking for an experienced ML Ops Engineer to build, automate, and maintain scalable machine ... Experience with Apache Airflow, Databricks, Spark, or Kafka. * Knowledge of LLMOps/GenAI deployment ...
We are looking for an experienced ML Ops Engineer to build, automate, and maintain scalable machine ... Experience with Apache Airflow, Databricks, Spark, or Kafka. * Knowledge of LLMOps/GenAI deployment ...
We are looking for an experienced ML Ops Engineer to build, automate, and maintain scalable machine ... Experience with Apache Airflow, Databricks, Spark, or Kafka. * Knowledge of LLMOps/GenAI deployment ...
We are looking for an experienced ML Ops Engineer to build, automate, and maintain scalable machine ... Experience with Apache Airflow, Databricks, Spark, or Kafka. * Knowledge of LLMOps/GenAI deployment ...
We are looking for an experienced ML Ops Engineer to build, automate, and maintain scalable machine ... Experience with Apache Airflow, Databricks, Spark, or Kafka. * Knowledge of LLMOps/GenAI deployment ...
We are looking for an experienced ML Ops Engineer to build, automate, and maintain scalable machine ... Experience with Apache Airflow, Databricks, Spark, or Kafka. * Knowledge of LLMOps/GenAI deployment ...
We are looking for an experienced ML Ops Engineer to build, automate, and maintain scalable machine ... Experience with Apache Airflow, Databricks, Spark, or Kafka. * Knowledge of LLMOps/GenAI deployment ...
We are looking for an experienced ML Ops Engineer to build, automate, and maintain scalable machine ... Experience with Apache Airflow, Databricks, Spark, or Kafka. * Knowledge of LLMOps/GenAI deployment ...
We are looking for an experienced ML Ops Engineer to build, automate, and maintain scalable machine ... Experience with Apache Airflow, Databricks, Spark, or Kafka. * Knowledge of LLMOps/GenAI deployment ...
We are looking for an experienced ML Ops Engineer to build, automate, and maintain scalable machine ... Experience with Apache Airflow, Databricks, Spark, or Kafka. * Knowledge of LLMOps/GenAI deployment ...
Databricks Engineer information
See Pewaukee, WI salary details
$58.2K - $71K
14% of jobs
$78.6K is the 25th percentile. Wages below this are outliers.
$71K - $83.8K
19% of jobs
$83.8K - $96.5K
12% of jobs
The median wage is $100.9K / yr.
$96.5K - $109.3K
17% of jobs
$109.3K - $122.1K
12% of jobs
$124.3K is the 75th percentile. Wages above this are outliers.
$122.1K - $134.8K
14% of jobs
$134.8K - $147.6K
7% of jobs
$147.6K - $160.3K
3% of jobs
$160.3K - $173.1K
0% of jobs
$173.1K - $185.9K
1% of jobs
$185.9K - $198.6K
2% of jobs
$58.2K
$109.2K
$198.6K
How much do databricks engineer jobs pay per year?
As of Sep 10, 2026, the average yearly pay for databricks engineer in Pewaukee, WI is $109,237.00, according to ZipRecruiter salary data. Most workers in this role earn between $78,800.00 and $129,700.00 per year, depending on experience, location, and employer.
What is a Databricks engineer?
A Databricks Engineer is a data engineering professional who specializes in using the Databricks platform to build, manage, and optimize data pipelines and analytics solutions. They work with big data technologies like Apache Spark, Delta Lake, and cloud services to process and analyze large datasets efficiently. Their role often involves developing ETL (extract, transform, load) workflows, setting up data lakes, and ensuring data quality and performance for business intelligence and machine learning applications.
What are the key skills and qualifications needed to thrive as a Databricks engineer?
To thrive as a Databricks Engineer, you need strong expertise in big data processing, cloud platforms (like AWS or Azure), and proficiency with languages such as Python, SQL, and Scala, often supported by a degree in computer science or a related field. Familiarity with Apache Spark, Databricks Workspace, version control systems like Git, and relevant Databricks certifications are typically required. Strong analytical thinking, collaboration, and effective communication skills help you understand business needs and work seamlessly with data teams. These skills ensure efficient data pipeline development, scalable analytics solutions, and successful integration of Databricks into organizational workflows.
What are some common challenges faced by Databricks engineers when working with large-scale data pipelines?
Databricks Engineers often encounter challenges related to optimizing the performance and reliability of large-scale data pipelines. These can include efficiently managing cluster resources, handling data partitioning to prevent bottlenecks, and troubleshooting job failures due to resource constraints or data quality issues. Collaboration with data scientists, analysts, and DevOps teams is essential to ensure seamless integration and deployment of production workflows. Staying current with evolving Databricks features and best practices also plays a key role in overcoming these challenges.
How much does a Databricks engineer make?
A Databricks engineer's salary typically ranges from $90,000 to $150,000 annually, depending on experience, location, and skill level. Senior roles or those with specialized skills in Spark, cloud platforms, and data engineering can earn higher compensation, often including bonuses and benefits.
Is a Databricks engineer in demand?
Databricks engineers are in high demand due to the growing adoption of cloud-based data analytics and machine learning platforms. They typically require skills in Spark, SQL, and cloud environments like AWS or Azure, making them valuable in data-driven organizations across various industries.
What are popular job titles related to Databricks Engineer jobs in Pewaukee, WI?
For Databricks Engineer jobs in Pewaukee, WI, the most frequently searched job titles are:
What cities near Pewaukee, WI are hiring for Databricks Engineer jobs?
Cities near Pewaukee, WI with the most Databricks Engineer job openings:
ML Ops Engineer
Mequon, WI
Techvilla Solutions
 • IT Services • 51 - 200 employees51 - 200 employees
Full-time
Posted 21 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.
- 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.
- 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.
Bachelor’s degree in Computer Science, Engineering, Data Science, or a related technical field, or equivalent practical experience.
About Techvilla Solutions
Sourced by ZipRecruiter
Industry
It services
Company size
51 - 200 Employees
Headquarters location
CA, US
Year founded
2006