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Sr Data Engineer Jobs in Madison, WI (NOW HIRING)

Urus Group LP

Senior AI/ML Engineer

Watertown, WI · On-site +1

$99K - $136K/yr

Turn decades of data into intelligence that helps feed the world. VAS is the Operating System of ... We are seeking a Senior AI/ML Engineer to lead the building of scalable real-time production-grade ...

Farm Systems

Senior AI/ML Engineer

Watertown, WI · On-site

$99K - $136K/yr

Turn decades of data into intelligence that helps feed the world. VAS is the Operating System of ... We are seeking a Senior AI/ML Engineer to lead the building of scalable real-time production-grade ...

Husch Blackwell Llp

Senior Software Engineer

Madison, WI · On-site +1

$123K - $162K/yr

The Senior Software Engineer designs, builds, and maintains the technical systems and application ... Collaborate with Information Engineers, designers, and data scientists to deliver engaging data ...

Husch Blackwell LLP

Senior Software Engineer

Madison, WI · On-site +1

$123K - $162K/yr

The Senior Software Engineer designs, builds, and maintains the technical systems and application ... Collaborate with Information Engineers, designers, and data scientists to deliver engaging data ...

Phoenix Industrial Inc

Sr. Project Engineer

Madison, WI · On-site

$99K - $130K/yr

Overview: The Sr. Project Engineer role will oversee and execute the project controls and ... Direct Field Engineers to gather and prepare data for submittal or transmittal to the customer ...

Paradigm

Senior Applied ML Engineer

Middleton, WI · Remote

$125K - $183K/yr

We are looking for a Senior Applied ML Engineer to be part of revolutionizing these industries. We ... construction data. * Build scalable ML pipelines and backend services that integrate into ...

HealthX Ventures

Senior Staff Engineer

Madison, WI · On-site

$200 - $250/hr

This is the most senior individual contributor role on our engineering team. You'll influence ... APIs, data models, infrastructure, deployment, scalability, reliability, and long‑term ...

Recovery.com

Senior Staff Engineer

Madison, WI · On-site

$105K - $144K/yr

This is the most senior individual contributor role on our engineering team. You'll influence ... APIs, data models, infrastructure, deployment, scalability, reliability, and long-term ...

Recovery.com

Senior Staff Engineer

Madison, WI · On-site

$105K - $144K/yr

This is the most senior individual contributor role on our engineering team. You'll influence ... APIs, data models, infrastructure, deployment, scalability, reliability, and long-term ...

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Showing results 41-60

All JobsSr Data Engineer JobsSr Data Engineer Jobs in Madison, WI

Sr Data Engineer information

See Madison, WI salary details

$81.6K

$127.3K

$176.4K

How much do sr data engineer jobs pay per year?

As of Sep 7, 2026, the average yearly pay for sr data engineer in Madison, WI is $127,311.00, according to ZipRecruiter salary data. Most workers in this role earn between $106,800.00 and $145,100.00 per year, depending on experience, location, and employer.

What is a Sr data engineer?

Sr Data Engineers, or Senior Data Engineers, are experienced professionals responsible for designing, building, and maintaining scalable data pipelines and architectures. They work with large datasets, ensuring data quality, reliability, and accessibility for analytics and business intelligence purposes. Sr Data Engineers collaborate with data scientists, analysts, and other stakeholders to implement data solutions that support decision-making and business growth. Their expertise often includes proficiency in programming languages like Python or Java, experience with big data tools such as Hadoop or Spark, and a deep understanding of database systems.

How do Sr data engineers typically collaborate with data scientists and analysts within a project team?

Sr Data Engineers play a crucial role in bridging the gap between raw data and actionable insights. They work closely with data scientists and analysts to understand data requirements, design robust data pipelines, and ensure the reliability and scalability of data infrastructure. Regular collaboration involves translating analytical needs into technical specifications, optimizing data flow, and troubleshooting data issues. This teamwork ensures that data-driven projects progress smoothly and that the analytical team has timely access to clean, well-structured data.

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

To thrive as a Sr Data Engineer, you need expertise in data architecture, ETL processes, programming (such as Python or Scala), and a strong background in computer science or a related field. Familiarity with big data technologies like Hadoop, Spark, cloud platforms (AWS, Azure, GCP), and database management systems, along with relevant certifications, is typically required. Advanced problem-solving abilities, attention to detail, and strong collaboration skills help set top performers apart in this role. These skills and qualities ensure the efficient design, implementation, and maintenance of robust data pipelines that enable data-driven decision-making across the organization.

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

AspectSr Data EngineerData Engineer
Required CredentialsBachelor's degree in CS or related field; 3+ years experience; SQL, Python, SparkBachelor's degree in CS or related field; 1-3 years experience; SQL, Python, Spark
Work EnvironmentCollaborates with data scientists, analysts; designs scalable data pipelinesBuilds and maintains data pipelines; supports data analysis
Employer & Industry UsageTech companies, finance, healthcare; used for complex data projectsStartups, enterprises; used for data collection and processing

The main difference between a Sr Data Engineer and a Data Engineer lies in experience level, responsibilities, and complexity of projects. Sr Data Engineers typically have more experience, handle more complex data architecture, and mentor junior staff, whereas Data Engineers focus on building and maintaining data pipelines. Both roles are essential in data-driven organizations, but the senior role involves greater technical leadership and strategic planning.

What are popular job titles related to Sr Data Engineer jobs in Madison, WI?

For Sr Data Engineer jobs in Madison, WI, the most frequently searched job titles are:

What job categories do people searching Sr Data Engineer jobs in Madison, WI look for?

The top searched job categories for Sr Data Engineer jobs in Madison, WI are:

What cities near Madison, WI are hiring for Sr Data Engineer jobs?

Cities near Madison, WI with the most Sr Data Engineer job openings:

Sr Data Engineer jobs near you
Infographic showing various Sr Data Engineer job openings in Madison, WI as of August 2026, with employment types broken down into 1% As Needed, 82% Full Time, 13% Part Time, and 4% Contract. Highlights an 87% Physical, 3% Hybrid, and 10% Remote job distribution, with an average salary of $127,311 per year, or $61.2 per hour.

Senior AI/ML Engineer

Urus Group LP

Watertown, WI • On-site, Remote

$99K - $136K/yr

Full-time

Posted 27 days ago

Key responsibilities

  • Lead the building of scalable real-time production-grade AI/ML applications for dairy farms.

  • Identify opportunities to apply AI to improve efficiency, growth, and customer value, and demonstrate AI capabilities to stakeholders.

  • Build, deploy, and monitor AI/ML models in production environments, ensuring their integration into real-time applications.

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.

About Us
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.

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