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Intern Streaming Data Engineer Jobs in Wisconsin

Manufacturing Engineer Intern

Appleton, WI

$16 - $20.75/hr

Join Our Dynamic Team as a Manufacturing Engineering Intern! Shape the Future of Innovation and ... insightful data. * Charting Triumph: Gantt Charts aren't just diagrams; they're the roadmaps of ...

AWS Data Architect

Neenah, WI · On-site

$64.50 - $82.75/hr

... streaming solutions. * Define data ingestion, transformation, and storage strategies using AWS ... Collaborate with data engineers, analysts, and business teams to translate business requirements ...

Intern Mechanical Engineer

Pewaukee, WI

$18.25 - $24.75/hr

Summary The Mechanical Engineering Intern supports the mechanical design and development of ... Build, assemble, and help test prototypes in the lab. * Assist with mechanical testing, data ...

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Showing results 1-20

Intern Streaming Data Engineer information

What is the difference between Intern Streaming Data Engineer vs Intern Data Analyst?

AspectIntern Streaming Data EngineerIntern Data Analyst
Required SkillsKnowledge of streaming platforms (e.g., Kafka, Spark Streaming), programming (Python, Java), data pipeline developmentData analysis, SQL, Excel, basic statistical skills
Work EnvironmentDeveloping real-time data pipelines, working with big data toolsAnalyzing stored data, generating reports and insights
Industry UsageTech, finance, e-commerce companies focusing on real-time data processingMarketing, business intelligence, research departments

The Intern Streaming Data Engineer focuses on building and maintaining real-time data pipelines using streaming technologies, requiring programming and big data skills. In contrast, the Intern Data Analyst primarily analyzes stored data to generate insights, emphasizing statistical and reporting skills. Both roles are common in data-driven industries but serve different functions within data management and analysis.

What does an Intern Streaming Data Engineer do?

An Intern Streaming Data Engineer assists in designing, developing, and maintaining systems that process real-time data streams. They typically work with technologies like Apache Kafka, Apache Flink, or Spark Streaming to collect, process, and analyze data as it arrives. Their responsibilities may include writing code, troubleshooting data pipelines, and collaborating with senior engineers to ensure data flows efficiently. The role is ideal for students or recent graduates looking to gain hands-on experience with big data and real-time analytics.

What types of projects or tasks can an Intern Streaming Data Engineer expect to work on during their internship?

As an Intern Streaming Data Engineer, you can expect to work on projects involving the development, testing, and optimization of real-time data pipelines. Typical tasks may include assisting with the integration of streaming platforms like Apache Kafka or AWS Kinesis, writing and debugging code to process large volumes of incoming data, and collaborating with senior engineers to ensure data quality and reliability. You'll often work within a team of data engineers and analysts, gaining hands-on experience with the latest big data tools and contributing to solutions that support real-time analytics and business decision-making.

What are the key skills and qualifications needed to thrive as an Intern Streaming Data Engineer, and why are they important?

To thrive as an Intern Streaming Data Engineer, you typically need foundational knowledge in computer science, data engineering concepts, and familiarity with real-time data processing. Experience with tools like Apache Kafka, Apache Flink, or Spark Streaming, and programming languages such as Python or Java, is often preferred. Strong problem-solving skills, attention to detail, and effective teamwork and communication abilities help set candidates apart. These skills and qualifications are crucial for efficiently building, maintaining, and troubleshooting streaming data pipelines in dynamic data-driven environments.
What are popular job titles related to Intern Streaming Data Engineer jobs in Wisconsin? For Intern Streaming Data Engineer jobs in Wisconsin, the most frequently searched job titles are:
What job categories do people searching Intern Streaming Data Engineer jobs in Wisconsin look for? The top searched job categories for Intern Streaming Data Engineer jobs in Wisconsin are:
Forward Deployed Engineer- Snowflake

Forward Deployed Engineer- Snowflake

Deloitte

Milwaukee, WI

Other

Posted 10 days ago


Deloitte rating

8.1

Company rating: 8.1 out of 10

Based on 86 frontline employees who took The Breakroom Quiz

55th of 139 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.

Recruiting for this role ends on 10/30/2026.

Work you'll do

As a Snowflake 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.
  • 3+ 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 Snowflake including hands-on experience with one of the following key platforms; Cortex AI, Cortex LLM Functions, Cortex Agents, Arctic Embed
  • 1+ years of experience leading project workstreams/engagements and translating business problems into AI solutions
  • 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 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 $134,500 to $265,100.

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.

Recruiting for this role ends on 10/30/2026.

Work you'll do

As a Snowflake 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.
  • 3+ 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 Snowflake including hands-on experience with one of the following key platforms; Cortex AI, Cortex LLM Functions, Cortex Agents, Arctic Embed
  • 1+ years of experience leading project workstreams/engagements and translating business problems into AI solutions
  • 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 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 $134,500 to $265,100.

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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