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Data Analytics Engineer Jobs in Minnesota (NOW HIRING)

One Tech

Data Analyst

Minneapolis, MN

$73K - $78K/yr

One Tech Engineering is searching for a Data Analyst for a position located in Denver, Colorado, or Minneapolis, Minnesota. The Data Analyst will be supporting energy efficiency programs by ensuring ...

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TriOptus LLC

Data Engineer | TELECOMMUTE

Minneapolis, MN · On-site +1

$119K - $143K/yr

We are a team of 9 Data Engineers and Analysts + Engineering Managers/Leaders * We have 1 product owner on the team and work with several others directly * We have a Scrum Master aligned as well ...

Ztek Consulting INC

Lead Data Engineer

Minneapolis, MN · On-site

... Series Analysis, Linear and Non-linear Modeling, Data Mining, Optimization and Simulation and Data Engineering (Snowflake, Oracle and SQL) 5 years of experience in designing data conformation from ...

Sovos

Senior Data Engineer

Hopkins, MN · On-site

$107K - $146K/yr

The Senior Data Engineer will play a crucial role in building a financial data platform, managing ... with the Analytics Engineer on business-layer model design to ensure technical outputs map ...

RELX

AI Data Analyst

Minneapolis, MN · On-site

... analytics engineering, data operations, or data quality roles. * Good understanding of data quality principles and how poor data impacts downstream systems. * Experience working with structured and ...

Pwc

Data Engineer - Senior Associate

Minneapolis, MN

$77K - $202K/yr

Industry/Sector Not Applicable Specialism Data, Analytics & AI Management Level Senior Associate & Summary The Opportunity As a Data Engineer - Senior Associate, you will focus on designing and ...

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All JobsData Analytics Engineer JobsData Analytics Engineer Jobs in Minnesota

Data Analytics Engineer information

See Minnesota salary details

$43.6K

$127K

$173.8K

How much do data analytics engineer jobs pay per year?

As of Jul 15, 2026, the average yearly pay for data analytics engineer in Minnesota is $127,046.00, according to ZipRecruiter salary data. Most workers in this role earn between $112,100.00 and $134,700.00 per year, depending on experience, location, and employer.

How do Data Analytics Engineers typically collaborate with data scientists and business stakeholders on projects?

Data Analytics Engineers play a crucial role in bridging the gap between raw data and actionable insights by building, optimizing, and maintaining data pipelines. They often work closely with data scientists to ensure data is clean, accessible, and structured for advanced analytics or machine learning models. Additionally, they collaborate with business stakeholders to understand reporting requirements and ensure that data solutions align with organizational objectives. Regular communication and cross-functional teamwork are essential aspects of this role, as engineers must translate business needs into technical specifications and deliver reliable data products.

Can a data engineer make 200k?

Data engineers can earn $200,000 or more annually, especially with experience, advanced skills in cloud platforms, big data tools, and certifications. Salaries vary by location, industry, and company size, with senior roles and those in high-demand markets more likely to reach or exceed this level.

What engineers make $500,000?

Senior data analytics engineers with extensive experience, advanced skills in data modeling, machine learning, and proficiency with tools like Python, SQL, and cloud platforms can reach salaries of $500,000 or more, especially in high-cost-of-living areas or within large tech companies. Achieving this level often requires a combination of technical expertise, leadership roles, and sometimes equity compensation.

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

To thrive as a Data Analytics Engineer, you need strong proficiency in data modeling, SQL, and statistical analysis, typically supported by a degree in computer science, statistics, or a related field. Familiarity with tools such as Python, R, Apache Spark, Tableau, and cloud data platforms like AWS or Google BigQuery is essential, along with relevant certifications. Excellent problem-solving, communication, and collaboration skills help you translate data insights into actionable business solutions. These skills and qualities are crucial for designing robust data pipelines and enabling data-driven decision-making across organizations.

Is 40 too late for data science?

Data Analytics Engineers and data science professionals can successfully transition into the field at age 40 or older, as skills such as programming, statistical analysis, and experience with tools like Python or SQL are valuable regardless of age. Many employers value diverse experience and lifelong learning, and certifications or online courses can help enhance credentials at any age.

What is the difference between Data Analytics Engineer vs Data Scientist?

AspectData Analytics EngineerData Scientist
CredentialsBachelor's or master's in CS, Data Science, or related fields; certifications like Google Data AnalyticsBachelor's or master's in CS, Statistics, or related fields; certifications like Certified Data Scientist
Work EnvironmentFocus on building data pipelines, dashboards, and analytics toolsFocus on statistical modeling, machine learning, and data exploration
Employer & Industry UsageUsed across tech, finance, healthcare for data infrastructure and analyticsCommon in research, product development, and advanced analytics teams

While both roles work with data, Data Analytics Engineers primarily develop data infrastructure and tools for analysis, whereas Data Scientists focus on statistical modeling and machine learning to generate insights. They often collaborate but have distinct technical focuses.

What does a data analytics engineer do?

A data analytics engineer designs, builds, and maintains data pipelines and systems to collect, process, and analyze large datasets. They use tools like SQL, Python, and cloud platforms to enable data-driven decision-making and often collaborate with data scientists and business teams to deliver actionable insights.
What are the most commonly searched types of Data Analytics Engineer jobs in Minnesota? The most popular types of Data Analytics Engineer jobs in Minnesota are:
What are popular job titles related to Data Analytics Engineer jobs in Minnesota? For Data Analytics Engineer jobs in Minnesota, the most frequently searched job titles are:
What job categories do people searching Data Analytics Engineer jobs in Minnesota look for? The top searched job categories for Data Analytics Engineer jobs in Minnesota are:
What cities in Minnesota are hiring for Data Analytics Engineer jobs? Cities in Minnesota with the most Data Analytics Engineer job openings:
Data Analytics Engineer jobs near you
Data Analyst

Data Analyst

One Tech

Minneapolis, MN

$73K - $78K/yr

Other

Posted yesterday

Job description

Job Description One Tech Engineering is searching for a Data Analyst for a position located in Denver, Colorado, or Minneapolis, Minnesota. The Data Analyst will be supporting energy efficiency programs by ensuring data quality and supporting data governance practices. The candidate must be a US citizen or hold a green card.

The candidate should have at least 3 years of related experience. Data Analyst Responsibilities: Review and validate incoming data for accuracy and completeness. Identify data gaps, inconsistencies, and issues within data pipelines.

Collaborate with IT to develop and implement data validation rules and resolve pipeline issues. Build, maintain, and update data pipelines. Develop and enhance Power BI dashboards and reporting tools.

Document data dictionaries, data flows, and validation rules. Work with internal stakeholders to gather reporting requirements and understand business needs. Translate complex data into clear, meaningful insights for business users.

Support self-service analytics and provide training to end users as needed. Requirements of the Data Analyst: 3+ years of related experience. Strong interest in data analytics or data science.

Comfortable working with messy, incomplete, or undocumented data. Proficiency in SQL, Python, and Power BI. Experience developing or working with data pipelines is preferred.

Familiarity with Jira is a plus. Experience with Databricks is a plus.

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