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Data Analytics Engineer Jobs in Minnesota (NOW HIRING)

Coloplast

Data & Analytics, Manager

Minneapolis, MN · On-site

Manage a team of Data Analysts and Engineers * Hire, develop, and mentor analytics talent toward emerging leadership roles * Foster a culture of analytics excellence and establish team standards for ...

Frch Nelson

Senior Analytics Engineer

Minneapolis, MN · On-site

Migrate core data infrastructure from legacy systems to modern platforms, supporting the business ... engineering, BI, or analytics delivery roles * Proven experience delivering production data 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 Aug 5, 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.

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.

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 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
Infographic showing various Data Analytics Engineer job openings in Minnesota as of July 2026, with employment types broken down into 57% Full Time, and 43% Contract. Highlights an 100% In-person job distribution, with an average salary of $127,046 per year, or $61.1 per hour.

IT-Analytics Engineer

Cretex Companies, Inc.

Brooklyn Park, MN • On-site

$90K - $140K/yr

Full-time

Medical, Dental, Vision, Life, Retirement, PTO

Posted 4 days ago

Job description

Overview
Position Summary
Analytics Engineer is responsible for designing, building, and optimizing a modern manufacturing data platform that transforms complex operational data into trusted, analytics-ready solutions. The position combines hands-on data engineering with technical leadership, leveraging Snowflake, DBT, Matillion, and CI/CD best practices to develop scalable, high-performing data pipelines and models. Working closely with business stakeholders and product owners, the individual will ensure data quality, governance, and observability while building semantic data layers that support reporting, self-service analytics, and future AI-driven capabilities. The ideal candidate brings deep expertise in modern data architecture, strong communication skills, and experience delivering scalable data products that enable business insights and operational excellence.
Stack: Snowflake, Snowflake AI/Cortex, DBT, Matillion, Dimensional Modeling, Data Vault 2.0, GitHub/CI-CD, Power BI
Responsibilities
Essential Job Functions
  • Design, develop, and maintain scalable data ingestion and orchestration processes using Matillion or similar enterprise ETL/ELT tools to integrate data from complex manufacturing systems into Snowflake.
  • Build, deploy, and support end-to-end data transformation pipelines using DBT and Snowflake, moving data through Bronze (raw), Silver (integrated), and Gold (analytics-ready) layers.
  • Develop and maintain Data Vault 2.0 models and related data architecture standards to ensure data is auditable, scalable, and adaptable to evolving business systems and ERP environments.
  • Create and optimize dimensional models, star schemas, and semantic data layers that support self-service analytics and high-performance reporting in Power BI and other analytical tools.
  • Design, implement, and manage CI/CD processes, source control standards, and automated deployment pipelines using GitHub Actions, Azure DevOps, or similar technologies to ensure reliable and repeatable releases.
  • Establish and maintain monitoring, logging, alerting, and observability capabilities to proactively identify, troubleshoot, and resolve data pipeline and platform issues.
  • Implement and maintain automated data quality controls, validation testing, and observability frameworks to ensure the accuracy, completeness, and reliability of enterprise data assets.
  • Partner with Data Product Owners, business stakeholders, and cross-functional teams to evaluate technical requirements, assess solution feasibility, and translate business needs into actionable technical deliverables.
  • Provide technical leadership and guidance on data platform architecture, development standards, best practices, and documentation to ensure scalable and maintainable solutions.
  • Define and promote architectural patterns that support future AI, machine learning, and advanced analytics capabilities within the Snowflake ecosystem, including semantic layers, secure data access, search, and agent-based workflows.
  • Analyze and optimize Snowflake compute utilization, data processing performance, and SQL query execution to improve platform efficiency, scalability, and end-user experience.
  • Collaborate effectively across technical and business teams, communicating complex concepts clearly and contributing to the successful delivery of enterprise data and analytics initiatives.

Qualifications
Minimum Requirements, Education & Experience (incl. KSA's and certifications)
  • Bachelor's degree in Computer Science, Engineering, or a related field
  • 6 years of data engineering and/or analytics engineering experience with demonstrated expertise in Snowflake and DBT.
  • Experience querying and consuming data from Microsoft SQL Server (MSSQL) and REST APIs.
  • Understanding of data connectivity methods, including ODBC, ADO, and JDBC. Experience with PostgreSQL, MySQL, or MariaDB is a plus.
  • Expert experience using Git-based source control workflows and building automated CI/CD deployment pipelines for data platforms.
  • Proven experience designing and implementing Medallion/Lakehouse data architectures and dimensional data models.
  • Working knowledge and experience with Data Vault 2.0 architecture is preferred.
  • Demonstrated ability to communicate effectively with stakeholders at all levels of the organization and collaborate successfully across cross-functional teams.
  • Proven ability to gather requirements, translate business needs into technical solutions, and work effectively with diverse team members and stakeholders.

Desirable Criteria & Qualifications
  • Experience working with manufacturing data domains, including Bills of Materials (BOMs), Inventory, Sales and Work Orders, Supply Chain, Quality (NCRs/CAPA), Labor and Scrap Reporting, Machine Usage, and Efficiency Metrics.
  • Familiarity with machine interfaces and streaming data ingestion technologies.
  • Hands-on experience with Snowflake performance tuning, governance, role-based access controls, and platform capabilities that support scalable analytics and AI-ready data products.
  • Familiarity with Snowflake AI capabilities, including Cortex AI (CoCo), Cortex Analyst, Cortex Search, Snowflake CoWork, Snowpark, Agents, or related features that support governed AI/ML use cases within the data platform.
  • Experience preparing governed, well-modeled data products for AI/ML and agentic use cases, including metadata management, semantic descriptions, access controls, and business-friendly data definitions.
  • Experience with analytics visualization tools, such as Power BI, and an understanding of how downstream consumers interact with data products.
  • Ability to write custom Python scripts to support integrations when out-of-the-box tools do not meet business or technical requirements.

#LI-MH1
Pay Range
USD $90,000.00 - USD $140,000.00 /Yr.
Pay Range Details
This pay range reflects the base hourly rate or annual salary for positions within this job grade, based on our market-based pay structures. Actual compensation will depend on factors such as skills, relevant experience, education, internal equity, business needs, and local market conditions. While the full hiring range is shared for transparency, offers are rarely made at the minimum or maximum of the range
Company Benefits
All Employees:
Our 401k retirement savings plan with a company match contribution; onsite health clinics, discretionary holiday bonus program (based on years of service), Cretex University, 24/7 employee assistance program with access to five confidential visits with a licensed counselor at no cost, wellness program with incentives, an employee death benefit, and employee sick and safe leave are available to all Cretex employees.
20+hours:
Cretex's medical benefit package includes: comprehensive medical insurance with access to virtual providers; dental insurance (Little Partners Dental benefit covers services 100 percent for children 12 and younger when seen by a Health Partners in network provider); vision insurance; a pre-tax health savings account, healthcare and dependent care pre-tax reimbursement accounts; paid holidays, paid time off; and our discretionary profit sharing program are available to employees working 20+ hours/week.
30+ hours:
Parental Leave, accident and critical illness benefits, optional employee, spouse, and child life; short and long term disability; company provided life insurance; and tuition assistance programs are available to employees working 30+ hours per week.
(Some benefits are subject to eligibility criteria.)
Applicants will receive consideration for employment regardless of their race, color, creed, religion, national origin, sex, sexual orientation, gender identity, disability, age, veteran status, marital status, family status, status with regard to public assistance, or any other protected status as required by law.
Our company uses E-Verify to confirm the employment and eligibility of all newly hired employees. To learn more about E-Verify, including your rights and responsibilities, please visit www.dhs.gov/E-Verify.

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