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Databricks Software Jobs in Wisconsin (NOW HIRING)

Senior AI/ML Engineer

Watertown, WI

$99K - $136K/yr

Experience with AWS and/or Databricks. * Experience or exposure to agentic architectures, MCP and AI orchestration frameworks. * Strong software engineering fundamentals and experience building ...

Senior AI/ML Engineer

Watertown, WI · On-site +1

$99K - $136K/yr

Experience with AWS and/or Databricks. * Experience or exposure to agentic architectures, MCP and AI orchestration frameworks. * Strong software engineering fundamentals and experience building ...

WI · On-site

$90 - $150/hr

Develop and maintain transformation logic and reusable data models using SQL, Python, Databricks, dbt, and related data engineering tools * Perform data wrangling, exploration, and discovery of ...

DevOps Engineer

Milwaukee, WI · On-site

$52 - $71.25/hr

Define, implement, and maintain CI/CD pipelines to automate software build, test, and deployment ... with Databricks. TRAVEL: None TO APPLY: Select "Apply" on this page and follow the prompts to ...

WI · On-site

$102.50 - $148.06/hr

  • Medical

  • Retirement

  • PTO

Strong hands-on software engineering across more than one stack (e.g. .NET, Python, Matlab, Flutter ... Nice to have * Experience with Databricks, Azure, Flutter, Matlab, or embedded / firmware ...

New

Senior Decision Intelligence Engineer (NBA)

Madison, WI · On-site

$107 - $147/hr

  • Medical

  • Dental

  • Vision

  • Life

  • Retirement

  • PTO

The Senior Decision Intelligence Engineer Is involved in all stages of software development ... Experience with Databricks, PySpark, and Delta Lake for large-scale ML or data pipelines processing ...

New

... software best practices (i.e., version control, continuous integration, test driven development) Experience with data engineering & visualization tools (e.g., Databricks, Spotfire) as well as cloud ...

Administer the Company's planning software; identify process gaps and lead improvements utilizing ... Power BI, Databricks, or similar data analysis and AI tools. * Demonstrated ability to manage ...

Administer the Company's planning software; identify process gaps and lead improvements utilizing ... Power BI, Databricks, or similar data analysis and AI tools. * Demonstrated ability to manage ...

Corporate FP&A Lead

Madison, WI · On-site

$120 - $170/hr

Administer the Company's planning software; identify process gaps and lead improvements utilizing ... Power BI, Databricks, or similar data analysis and AI tools.* Demonstrated ability to manage ...

WI · On-site

$120 - $150/hr

Design and implement scalable AI solutions leveraging platforms like Azure, Databricks, and Microsoft Fabric. * Thought Leadership: Represent EY in the market through events, publications, and client ...

WI · On-site

$180 - $240/hr

  • Medical

  • Dental

  • Vision

  • Life

  • Retirement

  • PTO

Partner with enterprise architecture, security, infrastructure, software engineering, analytics ... as Databricks, Delta Lake, Azure Data Services, Azure Data Factory, Azure Data Lake, Synapse, SQL ...

WI · On-site

$117.50 - $279.68/hr

  • Medical

  • Dental

  • Vision

  • Life

  • Retirement

  • PTO

... software development practices, version control systems, and agile methodologies * Experience working with cloud technologies (Azure) and handling large datasets (e.g., Azure Synapse, Databricks ...

New

Maintenance Planner

Milwaukee, WI · On-site

$110 - $170/hr

... Databricks, SQL, Python, Apache Spark, and comparable technologies. * Knowledge of software development lifecycle practices, including version control management, quality assurance, deployment ...

WI · On-site

$80 - $120/hr

Snowflake, BigQuery, Redshift, Databricks) * Internally motivated, self-starter with an analytical ... Familiarity with software engineering best practices -- Git/GitHub PR workflows, code review, CI/CD ...

New

Showing results 41-60

Databricks Software information

What is Databricks software?

Databricks Software is a unified analytics platform built on Apache Spark that provides tools for big data processing, machine learning, and collaborative data science. It enables organizations to store, manage, and analyze large datasets efficiently, supporting both batch and streaming data workloads. Databricks also offers collaborative notebooks, automated workflows, and integrations with cloud storage and data lakes, making it a popular choice for data engineering, data science, and business analytics teams.

What are the key skills and qualifications needed to thrive as a Databricks software engineer, and why are they important?

To thrive as a Databricks Software Engineer, you need strong programming skills in languages like Python, Scala, or Java, as well as a solid understanding of distributed computing and data engineering concepts. Familiarity with Databricks platform, Apache Spark, cloud services (such as AWS or Azure), and relevant certifications like Databricks Certified Data Engineer are highly valued. Excellent problem-solving abilities, collaboration, and effective communication are important soft skills for this role. These skills ensure efficient development, deployment, and optimization of big data solutions that drive business insights and innovation.

What are some common challenges faced by Databricks software engineers, and how can they be overcome?

Databricks Software Engineers often encounter challenges related to scaling big data pipelines, optimizing Spark workloads, and integrating diverse data sources. Navigating the complexity of distributed systems and managing cloud infrastructure can be demanding, especially when ensuring data reliability and security. To overcome these challenges, engineers typically collaborate closely with data scientists, DevOps, and platform teams, leverage Databricks' extensive documentation and community support, and adopt best practices such as version control and continuous integration. Regular knowledge sharing and staying updated with new features also help engineers succeed in this dynamic environment.

What is the difference between Databricks Software vs Data Engineer?

AspectDatabricks SoftwareData Engineer
Primary RolePlatform for data analytics and machine learningBuilds, maintains data pipelines and infrastructure
Required SkillsSQL, Spark, cloud platforms, data science basicsSQL, ETL, programming (Python, Scala), database management
Work EnvironmentCloud-based, collaborative data platformData teams, cloud or on-premises environments
CertificationsDatabricks certifications, cloud certificationsNone specific, often cloud or data certifications

While Databricks Software provides a platform for data analytics and machine learning, Data Engineers focus on building and maintaining data pipelines and infrastructure. Both roles often work together but have distinct responsibilities and skill sets within the data ecosystem.

Infographic showing various Databricks Software job openings in Wisconsin as of August 2026, with employment types broken down into 88% Full Time, 8% Part Time, and 4% Contract. Highlights an 88% Physical, 3% Hybrid, and 9% Remote job distribution.

$99K - $136K/yr

Full-time

Posted 7 days ago


Job description

Turn decades of data into intelligence that helps feed the world.

VAS is the Operating System of the modern dairy with decades of longitudinal data for the most productive cows in the world. We hold a dominant US market position, and an expanding global reach. 

We are seeking a Senior AI/ML Engineer to lead the building of scalable real-time production-grade applications that use AI/ML models to drive actionable intelligence on dairy farms. This is a strategic, hands-on position for an experienced technical leader who has a track record of shipping AI-enhanced customer applications and tooling used by engineering teams.

Our highly customizable on-farm systems give dairy owners unmatched flexibility in how they run their business. The right candidate sees that as a data challenge, where others will see it as an unsolvable mess. 

RESPONSIBILITIES

AI Enablement

  • Understand customer challenges and how integrating AI capabilities can help lead to solutions that have AI as a differentiator.

  • Identify opportunities to apply AI for efficiency, growth, and customer value

  • Drive awareness of AI capabilities and demonstrate how it can address customer needs, improve efficiency, reduce costs, and drive growth

  • Drive transformation from AI-Ad Hoc to AI-Native engineering practices

  • Serve as an AI technical SME, conduct R&D to meet the needs of our AI strategy

  • Continuously assess emerging AI tools and make data-driven recommendations

  • Measure & Accelerate Adoption: Establish KPIs, track progress from the current to 100% adoption, implement interventions to accelerate uptake and communicate impact

  • Build Center of Excellence: Create forums for knowledge sharing, celebrate wins, and foster peer-to-peer learning

  • Cross-functional communication, explaining technical tradeoffs to product, dairy science, and engineering leadership in plain language.

  • Working with other enterprise stakeholders, establish AI governance frameworks and guardrails covering compliance, security, privacy, and ethical AI practices, and embed them into development workflows

Core AI Engineering Skills

  • Comfort across the full method spectrum, from classical statistics and operations research through machine learning to modern generative AI, choosing the simplest tool that solves the problem.

  • Data-wrangling skill with messy, distributed, legacy enterprise data sources, including inconsistent schemas and incomplete records.

  • Feature-engineering and data preprocessing for both structured farm data and unstructured sources.

  • Model selection and evaluation, knowing when linear regression, optimization, or a lookup table beats a neural network.

  • Production deployment experience, shipping models into real time applications rather than notebooks.

  • Cloud AI infrastructure fluency, specifically Databricks and AWS.

  • Experiment design and statistical rigor, being able to prove a model or method actually improves outcomes.

  • Translating ambiguous business or technical requirements into working systems.

  • Agentic and MCP experience

Evaluation, Testing & Observability

  • Build unit and behavioral tests for agents, tools, and workflows.

  • Develop tooling for trace analysis, agent state debugging, and hallucination tracking.

  • Compare and benchmark agent orchestration frameworks for trade-offs in speed, reliability, and usability.

Model Fine-Tuning & MLOps

  • Integrate, deploy, fine tune and monitor models in production using cloud providers.

  • Set up agent logging, observability dashboards, and recovery workflows.

Front-end & User Experience

  • Collaborate with front-end developers or build user-facing components using React, TypeScript.

  • Ensure seamless user and agent interaction via UI and API bridges.

EDUCATION & EXPERIENCE

Your background might include software engineering, data engineering, data science, machine learning engineering or AI engineering. What matters most is demonstrated technical depth and a track record of building and deploying AI/ML solutions in production.

  • Significant hands-on experience designing, building and deploying production AI/ML solutions.

  • Strong experience working with complex data, including distributed systems, inconsistent schemas and incomplete or legacy datasets.

  • Experience with feature engineering, model selection, experimentation and evaluation.

  • Strong understanding of descriptive, predictive, prescriptive and generative AI approaches.

  • Experience selecting and applying techniques across statistics, operations research, machine learning and deep learning.

  • Demonstrated experience taking models from experimentation through production deployment and monitoring.

  • Experience with deep learning frameworks and cloud-based AI services.

  • Experience with AWS and/or Databricks.

  • Experience or exposure to agentic architectures, MCP and AI orchestration frameworks.

  • Strong software engineering fundamentals and experience building scalable, production-quality systems.

  • Ability to translate ambiguous requirements into working solutions and clearly communicate technical decisions and tradeoffs.

  • Bachelor's degree in Software Engineering, Computer Science, Data Science, AI/ML or a related field preferred.

For the past 40 years we've woken up each day to support those that never stop feeding the world - and we have no plans to quit. We set the standard for farm management solutions and fix our eyes on raising the bar to meet the next generation of expectations.

Our software and information solutions help collect and connect a farm's data - from herd management to feed performance, tracking and more. These insights are a source of truth, empowering producers and their trusted advisors to make profit-driven and sustainable management decisions.

Whether near or far, large or small, VAS is at the heart of your dairy.

VAS has deep roots in the industry through its origin within the URUS family of companies. As a holding company with cooperative and private ownership, URUS is a family of businesses at the heart of the dairy and beef industry - Alta Genetics, GENEX, Genetics Australia, Leachman Cattle, Jetstream, PEAK, SCCL, Trans Ova Genetics and VAS.  Each organization has its unique identity, products, and services. These companies work globally to provide cutting-edge dairy and beef genetics, customized reproductive services to maximize conceptions, dairy management information to take producers to the frontline of progressive dairy farming, and an array of products and services to help bovines reach their full genetic potential. URUS has 9 brands in 17 retail countries and employs nearly 2,800 people globally.