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

Ontech Talent

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Data & Integration Manager

Brookfield, WI · On-site

$150K - $175K/yr

  • Medical

  • Dental

  • Vision

  • Life

  • Retirement

Change Management & Learning Agility Experience & Qualifications: * 8+ years of progressive experience in data engineering, integration, analytics, application development, business intelligence, or ...

Baird

Data Integration Developer

Milwaukee, WI · On-site

As Baird continues to invest in data as a strategic asset, we are expanding our IT Data Integration team and seeking a Data Integration Developer to help build and support high-quality data solutions ...

Cielo

Senior Director - Client Data Solutions

Wauwatosa, WI · Remote

$103K - $139K/yr

Are you Strong experience in Data engineering / Data platforms & integrations? Do you have the ability to Identify most efficient and stable ways to extract client data, Ensure correct integration ...

Cielo

Senior Director - Client Data Solutions

Wauwatosa, WI · On-site +1

$103K - $139K/yr

Are you Strong experience in Data engineering / Data platforms & integrations? Do you have the ability to Identify most efficient and stable ways to extract client data, Ensure correct integration ...

Husch Blackwell Llp

Enterprise Data Analyst

Milwaukee, WI · On-site +1

  • Medical

  • Dental

  • Life

  • Retirement

  • PTO

Partner with the Data Engineering team to source, integrate, and validate data from across the Firm * Develop and apply data quality standards to ensure reliable, trustworthy outputs * Document data ...

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All JobsData Engineer JobsWeekend Data Engineer JobsWeekend Data Engineer Jobs in Milwaukee, WI

Weekend Data Engineer information

See Milwaukee, WI salary details

$43.8K

$127.8K

$174.9K

How much do weekend data engineer jobs pay per year?

As of Aug 13, 2026, the average yearly pay for weekend data engineer 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 is a weekend data engineer?

Weekend Data Engineers are professionals who work primarily on weekends to design, build, and maintain data systems and pipelines. Their responsibilities may include ensuring data flows smoothly between systems, managing databases, and supporting data analytics tasks during off-peak hours. This role is ideal for organizations that need data engineering support outside of standard business hours, such as companies with continuous operations or those processing large volumes of data over weekends. Weekend Data Engineers often collaborate remotely and may be part-time or contract workers.

What is the difference between Weekend Data Engineer vs Part-Time Data Analyst?

AspectWeekend Data EngineerPart-Time Data Analyst
Required CredentialsBachelor's in CS, Data Science, or related field; experience with data pipelinesBachelor's in related field; skills in data analysis and visualization
Work EnvironmentTech companies, data-driven organizations, remote or on-siteBusiness, marketing, or finance sectors; often remote or part-time
Employer & Industry UsageUsed in industries needing weekend data processing or maintenanceUsed in roles requiring part-time data insights and reporting

The Weekend Data Engineer focuses on building and maintaining data pipelines during weekends, often requiring technical skills and experience with data infrastructure. In contrast, a Part-Time Data Analyst primarily interprets data, creates reports, and provides insights on a flexible schedule. Both roles are suitable for flexible work arrangements but serve different functions within data teams.

What are the typical expectations and work patterns for a weekend data engineer?

As a Weekend Data Engineer, you’ll generally be responsible for maintaining, optimizing, and troubleshooting data pipelines and infrastructure during the weekend hours when production systems still require support. This role often involves monitoring data flows, addressing urgent issues, and ensuring data availability for business needs that operate on a 24/7 basis. You may collaborate remotely with on-call team members or communicate hand-offs to weekday staff, so strong documentation and clear communication are key. Weekend shifts can offer flexibility but may also require independent problem-solving, as fewer team members are available for immediate support.

What are the key skills and qualifications needed to thrive as a weekend data engineer?

To thrive as a Weekend Data Engineer, you need strong proficiency in data modeling, SQL, ETL processes, and programming languages like Python or Scala, typically supported by a degree in computer science or a related field. Familiarity with cloud platforms (such as AWS or Azure), data warehouse systems (like Redshift or Snowflake), and relevant certifications are often required. Excellent problem-solving, attention to detail, and the ability to work independently during off-hours are standout soft skills. These skills and qualities are crucial for maintaining reliable data pipelines, troubleshooting issues efficiently, and ensuring uninterrupted data services during weekend operations.

What are the most commonly searched types of Data Engineer jobs in Milwaukee, WI?

The most popular types of Data Engineer jobs in Milwaukee, WI are:

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

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

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

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

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

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

Weekend Data Engineer jobs near you
Infographic showing various Weekend Data Engineer job openings in Milwaukee, 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 $127,802 per year, or $61.4 per hour.

Senior Forward Deployed Engineer- AWS

Deloitte

Milwaukee, WI • On-site

$103K - $141K/yr

Full-time

Re-posted 24 days ago

Deloitte rating

8.2

Company rating: 8.2 out of 10

Based on 92 frontline employees who took The Breakroom Quiz

45th of 150 rated financial services

Job description

At Deloitte, Forward Deployed Engineers (FDE) don't just build AI solutions, they help clients turn AI ambition into enterprise-scale impact, pairing leading class engineering with pod-based delivery and vertical expertise. If you thrive at the intersection of product, engineering, problem-solving, and client impact, this role puts you at the forefront of AI transformations.

Work you'll do

As an AWS AI&Data FDE, you will work side by side with senior functional and technical client team members to rapidly prototype and deliver high-impact GenAI-enabled solutions. This requires a highly motivated practitioner who moves with speed and precision, building working software, engaging confidently with senior stakeholders and engineers to bring measurable business impact from day one. Additional responsibilities include:

Client Engagement

  • Embed with clients to identify business needs and translate high-value GenAI use cases into solutions.
  • Partner with leaders, product owners, architects, and engineers to align priorities and delivery.
  • Lead working sessions to shape solutions and drive client outcomes.
  • Prototype and deliver working AI solutions using industry expertise and emerging capabilities.
  • Contribute independently within an FDE pod while mentoring newer team members.

Solution Engineering

  • Build AI-enabled solutions, agentic platforms, and workflows across enterprise AI platforms.
  • Develop scalable AI engineering patterns, tool-use approaches, and human-in-the-loop controls.
  • Apply architecture decisions that balance quality, safety, latency, cost, and model risk.
  • Deliver production-quality code using strong practices in testing, CI/CD, logging, versioning, and documentation.
  • Design extensible functionality, support sprint sizing, and align solutions with senior team members.
  • Contribute reusable assets including code, prompt libraries, runbooks, and reference implementations.


The team

AI & Engineering leverages cutting-edge engineering capabilities to build, deploy, and operate integrated/verticalized sector solutions in software, data, AI, network, and hybrid cloud infrastructure. These solutions are powered by engineering for business advantage, transforming mission-critical operations. We enable clients to stay ahead with the latest advancements by transforming engineering teams and modernizing technology & data platforms. Our delivery models are tailored to meet each client's unique requirements.

Required qualifications 

  • Bachelor's degree (or equivalent) in Computer Science, Data Science or Engineering.
  • 5+ years of experience in software engineering, data engineering, data science, or analytics engineering. 
  • 1+ years of hands-on experience building and deploying GenAI/LLM-powered solutions in client or production environments
  • 1+ years of experience with AWS AI&Data including hands on experience with one of the following key platforms/products: Amazon Bedrock, Bedrock AgentCore, Strands Agents SDK, Knowledge Bases, Guardrails
  • 1+ years of experience with AWS Neptune and OpenSearch
  • 1+ years of experience leading project workstreams/engagements and translating business problems into AI solutions
  • At least 3 of 6 certifications from the following list: AWS Certified Cloud Practitioner, AWS Certified Solutions Architect (Associate), AWS Certified AI Practitioner (AIF-C01), AWS Certified Generative AI Developer (Professional - AIP-C01), AWS Certified Machine Learning Engineer (Associate - MLA-C01) or AWS Certified Data Engineer (Associate)
  • 1+ years of experience building reliable, maintainable, and well-documented code 
  • Ability to travel 50%, on average, based on the work you do and the clients and industries/sectors you serve
  • Limited immigration sponsorship may be available

Preferred qualifications

  • Experience with cloud environments (AWS, Azure, and/or Google Cloud) and common platform services (storage, compute, IAM, networking)
  • Demonstrated ability to work directly alongside client technical teams and program stakeholders in fast-paced, ambiguous delivery environments 
  • Data engineering experience with Spark, Airflow/dbt, streaming, data modeling or ML/data science background feature engineering, experimentation or model evaluation
  • Experience with MLOps/LLMOps practices: evaluation frameworks, model monitoring, and prompt management 
  • Experience with SageMaker fine-tuning (SFT and RFT) for domain SLMs
  • Experience integrating LLM solutions with enterprise systems via APIs, microservices, or event-driven architectures 
  • Experience operating within hybrid onshore/offshore teams 
  • Familiarity with security, privacy, and compliance considerations

The wage range for this role takes into account the wide range of factors that are considered in making compensation decisions including but not limited to skill sets; experience and training; licensure and certifications; and other business and organizational needs. The disclosed range estimate has not been adjusted for the applicable geographic differential associated with the location at which the position may be filled. At Deloitte, it is not typical for an individual to be hired at or near the top of the range for their role and compensation decisions are dependent on the facts and circumstances of each case. A reasonable estimate of the current range is $155,600 to 306,800.

You may also be eligible to participate in a discretionary annual incentive program, subject to the rules governing the program, whereby an award, if any, depends on various factors, including, without limitation, individual and organizational performance.


Qualifications:

At Deloitte, Forward Deployed Engineers (FDE) don't just build AI solutions, they help clients turn AI ambition into enterprise-scale impact, pairing leading class engineering with pod-based delivery and vertical expertise. If you thrive at the intersection of product, engineering, problem-solving, and client impact, this role puts you at the forefront of AI transformations.

Work you'll do

As an AWS AI&Data FDE, you will work side by side with senior functional and technical client team members to rapidly prototype and deliver high-impact GenAI-enabled solutions. This requires a highly motivated practitioner who moves with speed and precision, building working software, engaging confidently with senior stakeholders and engineers to bring measurable business impact from day one. Additional responsibilities include:

Client Engagement

  • Embed with clients to identify business needs and translate high-value GenAI use cases into solutions.
  • Partner with leaders, product owners, architects, and engineers to align priorities and delivery.
  • Lead working sessions to shape solutions and drive client outcomes.
  • Prototype and deliver working AI solutions using industry expertise and emerging capabilities.
  • Contribute independently within an FDE pod while mentoring newer team members.

Solution Engineering

  • Build AI-enabled solutions, agentic platforms, and workflows across enterprise AI platforms.
  • Develop scalable AI engineering patterns, tool-use approaches, and human-in-the-loop controls.
  • Apply architecture decisions that balance quality, safety, latency, cost, and model risk.
  • Deliver production-quality code using strong practices in testing, CI/CD, logging, versioning, and documentation.
  • Design extensible functionality, support sprint sizing, and align solutions with senior team members.
  • Contribute reusable assets including code, prompt libraries, runbooks, and reference implementations.


The team

AI & Engineering leverages cutting-edge engineering capabilities to build, deploy, and operate integrated/verticalized sector solutions in software, data, AI, network, and hybrid cloud infrastructure. These solutions are powered by engineering for business advantage, transforming mission-critical operations. We enable clients to stay ahead with the latest advancements by transforming engineering teams and modernizing technology & data platforms. Our delivery models are tailored to meet each client's unique requirements.

Required qualifications 

  • Bachelor's degree (or equivalent) in Computer Science, Data Science or Engineering.
  • 5+ years of experience in software engineering, data engineering, data science, or analytics engineering. 
  • 1+ years of hands-on experience building and deploying GenAI/LLM-powered solutions in client or production environments
  • 1+ years of experience with AWS AI&Data including hands on experience with one of the following key platforms/products: Amazon Bedrock, Bedrock AgentCore, Strands Agents SDK, Knowledge Bases, Guardrails
  • 1+ years of experience with AWS Neptune and OpenSearch
  • 1+ years of experience leading project workstreams/engagements and translating business problems into AI solutions
  • At least 3 of 6 certifications from the following list: AWS Certified Cloud Practitioner, AWS Certified Solutions Architect (Associate), AWS Certified AI Practitioner (AIF-C01), AWS Certified Generative AI Developer (Professional - AIP-C01), AWS Certified Machine Learning Engineer (Associate - MLA-C01) or AWS Certified Data Engineer (Associate)
  • 1+ years of experience building reliable, maintainable, and well-documented code 
  • Ability to travel 50%, on average, based on the work you do and the clients and industries/sectors you serve
  • Limited immigration sponsorship may be available

Preferred qualifications

  • Experience with cloud environments (AWS, Azure, and/or Google Cloud) and common platform services (storage, compute, IAM, networking)
  • Demonstrated ability to work directly alongside client technical teams and program stakeholders in fast-paced, ambiguous delivery environments 
  • Data engineering experience with Spark, Airflow/dbt, streaming, data modeling or ML/data science background feature engineering, experimentation or model evaluation
  • Experience with MLOps/LLMOps practices: evaluation frameworks, model monitoring, and prompt management 
  • Experience with SageMaker fine-tuning (SFT and RFT) for domain SLMs
  • Experience integrating LLM solutions with enterprise systems via APIs, microservices, or event-driven architectures 
  • Experience operating within hybrid onshore/offshore teams 
  • Familiarity with security, privacy, and compliance considerations

The wage range for this role takes into account the wide range of factors that are considered in making compensation decisions including but not limited to skill sets; experience and training; licensure and certifications; and other business and organizational needs. The disclosed range estimate has not been adjusted for the applicable geographic differential associated with the location at which the position may be filled. At Deloitte, it is not typical for an individual to be hired at or near the top of the range for their role and compensation decisions are dependent on the facts and circumstances of each case. A reasonable estimate of the current range is $155,600 to 306,800.

You may also be eligible to participate in a discretionary annual incentive program, subject to the rules governing the program, whereby an award, if any, depends on various factors, including, without limitation, individual and organizational performance.


Education:Bachelor's DegreeEmployment Type:

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