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Contract Data Engineering Jobs in Minnesota (NOW HIRING)

Data Engineer

Minneapolis, MN · On-site

$119K - $143K/yr

Data Engineer Richfield, MN 55423 (Local - Hybrid 2 Days/Week) 12+ Months Contract Project Description: You will be part of the Myads reporting team responsible for building the measurement ...

Data Engineer

Minneapolis, MN · On-site

$119K - $143K/yr

Data Engineer Richfield, MN 55423 (Local - Hybrid 2 Days/Week) 12+ Months Contract Project Description: You will be part of the Myads reporting team responsible for building the measurement ...

Data Engineer

Minneapolis, MN · Hybrid

$50 - $55/hr

Data Engineer Richfield, MN 55423 (Local - Hybrid 2 Days/Week) 12+ Months Contract Project Description: You will be part of the Myads reporting team responsible for building the measurement ...

Software Engineer

Minneapolis, MN · On-site

$68 - $73/hr

Contract-to-hire opportunity Minimum Qualifications * 6+ years of hands-on experience developing on ServiceNow * 5+ years of experience in data engineering or database engineering (or equivalent ...

Collaborate with Data Engineering on feature pipelines and data contracts. * Own production health: drift detection, performance regression, rollback strategies, and incident response." * 5+ years ...

Cloud Data Architect

Minneapolis, MN · On-site

$170K - $175K/yr

... data contracts, lineage) across different data organizations Reviews design and elevate ... with LLMs, prompt engineering, and agent frameworks (LangChain, AutoGen, CrewAI). Deep ...

Data Scientist-Jr

Rochester, MN · Hybrid

$102K - $138K/yr

... Engineering, Data Science, or related field. * Certifications: None required; cloud or ML-related certifications preferred. * Role requirements: On-Site 5 days * Due to US Government Contract ...

This is a 12+ month contract opportunity. Compensation: $55.00 - $62.00 per hour, W2, based on ... You will collaborate closely with Product Management, Ads Engineering, Analytics, and Data Science ...

... work together to engineer the extraordinary. This role can be located in Lafayette (CO ... Maintain and analyze contract data and documentation to support decision-making and historical ...

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Showing results 1-20

Contract Data Engineering information

Are data engineers still in demand?

Data engineers are currently in high demand due to the increasing reliance on data-driven decision making and the growth of big data technologies. Organizations seek professionals skilled in tools like SQL, Python, and cloud platforms to build and maintain data pipelines, making the role essential across many industries.

What is the difference between Contract Data Engineering vs Data Analyst?

AspectContract Data EngineeringData Analyst
Required SkillsSQL, Python, ETL, cloud platforms, data pipeline developmentSQL, Excel, data visualization, reporting tools
Work EnvironmentProject-based, technical teams, cloud or on-premises infrastructureBusiness units, reporting teams, often in office or remote
Industry UsageTech, finance, healthcare, retailMarketing, finance, healthcare, retail

Contract Data Engineers focus on building and maintaining data pipelines and infrastructure, requiring technical skills in programming and cloud platforms. Data Analysts interpret data, create reports, and visualize insights, often using different tools. While both roles work with data, Contract Data Engineering is more technical and infrastructure-oriented, whereas Data Analysts focus on data interpretation and business insights.

What engineers make $500,000?

Senior data engineers, especially those with extensive experience, specialized skills in cloud platforms, and expertise in big data tools, can earn $500,000 or more annually. High compensation is often associated with leadership roles, contract positions, or working in competitive industries like finance or technology. Achieving this level typically requires advanced certifications, a strong track record, and often working in high-cost-of-living areas or on high-stakes projects.

What is contract data engineering?

Contract data engineering refers to hiring data engineers on a temporary or project basis, rather than as full-time employees. Contract data engineers are responsible for designing, building, and maintaining data pipelines, databases, and other infrastructure to support data analytics and business needs. Companies often hire contract data engineers to handle specific projects, scale up teams quickly, or bring in specialized skills for a limited time. This arrangement offers flexibility for both the company and the engineer, and is common in industries with fluctuating data workloads or short-term projects.

Can a data engineer make 200k?

Senior data engineers with extensive experience, specialized skills in tools like Spark or cloud platforms, and working in high-cost-of-living areas can earn salaries of $200,000 or more. Compensation varies based on location, industry, and company size, with some roles offering bonuses and stock options that contribute to total earnings.

What are the key skills and qualifications needed to thrive as a Contract Data Engineer, and why are they important?

To thrive as a Contract Data Engineer, you need strong proficiency in data modeling, ETL processes, and programming languages such as Python or SQL, often supported by a degree in computer science or a related field. Familiarity with big data platforms (e.g., Hadoop, Spark), cloud services (AWS, Azure, GCP), and relevant certifications like Google Cloud Professional Data Engineer are typically required. Excellent problem-solving, adaptability, and effective communication are crucial soft skills in this role. These competencies enable efficient project delivery, seamless collaboration with stakeholders, and the ability to quickly adapt to new technical environments and client requirements.

What are some common challenges faced by contract data engineers and how can they be addressed?

Contract data engineers often face the challenge of quickly familiarizing themselves with a company's existing data infrastructure and processes. Since contracts are typically short-term, there is limited time to onboard, understand unique data pipelines, and build relationships with stakeholders. To address this, successful contract data engineers proactively communicate with team members, document their work thoroughly, and leverage their prior experience with a variety of tools and platforms. Flexibility and strong problem-solving skills are essential for adapting to new environments and delivering results efficiently.

What engineers make 300,000 a year?

Senior data engineers, especially those with extensive experience, advanced skills in cloud platforms, and expertise in big data tools like Spark and Hadoop, can earn $300,000 or more annually. High compensation is often associated with working in large organizations, in-demand industries, or holding leadership roles such as lead or principal data engineer.
What are the most commonly searched types of Data Engineering jobs in Minnesota? The most popular types of Data Engineering jobs in Minnesota are:
What are popular job titles related to Contract Data Engineering jobs in Minnesota? For Contract Data Engineering jobs in Minnesota, the most frequently searched job titles are:
What cities in Minnesota are hiring for Contract Data Engineering jobs? Cities in Minnesota with the most Contract Data Engineering job openings:
Infographic showing various Contract Data Engineering job openings in Minnesota as of July 2026, with employment types broken down into 1% As Needed, 62% Full Time, 19% Part Time, 1% Temporary, and 17% Contract. Highlights an 81% Physical, 2% Hybrid, and 17% Remote job distribution.
Contract role || Data Engineer || Minneapolis, MN (Onsite)

Contract role || Data Engineer || Minneapolis, MN (Onsite)

Inficare Technologies

Minneapolis, MN • On-site

$119K - $143K/yr

Full-time

Re-posted 21 days ago


Job description

Role : Data Engineer
Location: Minneapolis, MN Its day 1 onsite
Duration: Long term
Role Summary
A Data Engineer is responsible for designing, building, and maintaining the systems and infrastructure that enable organizations to collect, process, and analyze large volumes of data. The role focuses on transforming raw data into reliable, usable datasets that support analytics, reporting, and decision-making.