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Junior Data Engineering Jobs in Minnesota (NOW HIRING)

Data Scientist

Virginia, MN · On-site

$95 - $130/hr

Additionally, candidate should be capable of leading and mentoring more junior data scientists ... Utilize data engineering skills to integrate and deploy your analytical solutions, ensuring ...

Sr. Data Engineer

Edina, MN · On-site

$125K - $165K/yr

Mentor and guide junior team members. * Documentation & Standards : Establish and maintain comprehensive documentation and promote engineering best practices across the team. * Innovation : Evaluate ...

Data Architect

Virginia, MN · On-site

$140 - $210/hr

Lead the end‑to‑end design of data architectures supporting analytics, AI/ML, and operational ... Mentor junior architects and engineers while providing technical leadership across engagements ...

Data Engineer with AI/ML

Minnetonka, MN · On-site +1

$72K - $130K/yr

We are seeking a highly skilled and motivated Data Engineering Analyst with AI/ML expertise to ... Mentor junior engineers and foster knowledge-sharing within the team * Work independently to ...

You'''''ll partner closely with data engineers, business stakeholders, and fellow data scientists ... Mentor junior and mid-level Data Scientists through technical guidance, code reviews, and ...

IT Data Architect Specialist_3003

Minneapolis, MN · On-site

$66.50 - $85.50/hr

Databricks) and modern data engineering technologies. What you do (Hands on Data architect) Data ... Provide guidance and mentorship to junior architects and technical teams, fostering a culture of ...

Sr Data Scientist - Remote

Minnetonka, MN · On-site +1

$91K - $163K/yr

Mentor junior data scientists and analysts on analytical techniques, experimental design, and model ... programming in Python, R, or SQL for data modeling and analysis * 3 years of experience with ...

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Sr Data Scientist - Remote

Minnetonka, MN · On-site +1

$91K - $163K/yr

Mentor junior data scientists and analysts on analytical techniques, experimental design, and model ... programming in Python, R, or SQL for data modeling and analysis * 3+ years of experience with ...

New

Job Title: R&D Technician/Junior Quality Engineer We are seeking a dedicated R&D Technician or ... data. Additional Skills & Qualifications * Associate's degree in Engineering Technology ...

Job Title: R&D Technician/Junior Quality Engineer We are seeking a dedicated R&D Technician or ... data. Additional Skills & Qualifications * Associate's degree in Engineering Technology ...

... junior and mid-level data engineers. • Implement data quality checks, data validation rules, monitoring, logging, error handling, and restartability mechanisms. • Ensure adherence to data ...

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Junior Data Engineering information

See Minnesota salary details

$32.8K

$70.3K

$107.2K

How much do junior data engineering jobs pay per year?

As of Aug 29, 2026, the average yearly pay for junior data engineering in Minnesota is $70,321.00, according to ZipRecruiter salary data. Most workers in this role earn between $47,500.00 and $78,400.00 per year, depending on experience, location, and employer.

What does a junior data engineer do?

A Junior Data Engineer typically assists in designing, building, and maintaining data pipelines and databases to support analytics and business needs. They work with large datasets, ensuring data is collected, stored, and processed efficiently and accurately. Responsibilities often include data cleaning, ETL (Extract, Transform, Load) processes, and collaborating with data analysts and other engineers. Junior Data Engineers are usually early in their careers and work under the guidance of more experienced data engineers while developing their technical and problem-solving skills.

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

To thrive as a Junior Data Engineer, you need a solid understanding of data structures, SQL, and programming languages like Python or Java, often supported by a degree in computer science or a related field. Familiarity with ETL tools, cloud platforms (such as AWS or Azure), and data warehousing solutions is typically required. Strong problem-solving abilities, attention to detail, and effective communication help you excel in team environments and manage complex data workflows. These skills ensure you can reliably build, maintain, and optimize data pipelines that support organizational decision-making.

What are some typical challenges a junior data engineer may face when starting out, and how can they overcome them?

As a Junior Data Engineer, one common challenge is adapting to complex data infrastructure and unfamiliar tools or frameworks. You may also find it challenging to ensure data quality and consistency while working with large datasets. Collaborating closely with senior engineers and asking questions is key to overcoming these hurdles. Taking advantage of onboarding resources, documentation, and code reviews will help you learn best practices and improve your skills quickly. Embracing continuous learning and seeking feedback will set you up for long-term growth in data engineering.

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

AspectJunior Data EngineeringData Analyst
Required SkillsBasic SQL, Python, data pipeline knowledgeData visualization, SQL, Excel
CertificationsEntry-level certifications in data engineering or related fieldsCertifications in data analysis or visualization tools
Work EnvironmentData engineering teams, IT departmentsBusiness units, marketing, finance teams
Industry UsageBuilding and maintaining data pipelines and infrastructureInterpreting data, creating reports and dashboards

Junior Data Engineering focuses on developing and maintaining data pipelines and infrastructure, requiring skills in SQL and Python. Data Analysts interpret data and create reports, often using visualization tools. While both roles work with data, Junior Data Engineers handle data flow and storage, whereas Data Analysts focus on data interpretation and insights.

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 Junior Data Engineering jobs in Minnesota?

For Junior Data Engineering jobs in Minnesota, the most frequently searched job titles are:

What job categories do people searching Junior Data Engineering jobs in Minnesota look for?

The top searched job categories for Junior Data Engineering jobs in Minnesota are:

What cities in Minnesota are hiring for Junior Data Engineering jobs?

Cities in Minnesota with the most Junior Data Engineering job openings:

Infographic showing various Junior Data Engineering job openings in Minnesota as of August 2026, with employment types broken down into 1% As Needed, 83% Full Time, 12% Part Time, 3% Contract, and 1% Nights. Highlights an 85% Physical, 4% Hybrid, and 11% Remote job distribution, with an average salary of $70,321 per year, or $33.8 per hour.

$95 - $130/hr

Other

Posted 23 days ago


Job description

Career Opportunities with Elder Research

A great place to work.

Locations: USA-VA-Arlington OR USA-NC-Raleigh

Posting Date: 06/12/2026

Security Clearance Required: NONE

Remote Type: Hybrid

Time Type: Full time

Data Scientist - Hybrid (Raleigh, NC or Washington DC)

Elder Research Inc., a wholly owned subsidiary of MANTECH International Corporation, seeks a motivated, career and customer-oriented Data Scientist to join our team in Raleigh, NC or Washington DC. This role is hybrid, and candidates must be located in the Raleigh or Washington, DC market to support 1–2 days onsite per week.

This role is for a highly experienced and curious data scientist to lead the full-lifecycle development and deployment of analytical solutions at Elder. You will operate as a critical member of an analytics team, acting as a trusted advisor to diverse client partner team. The focus is on leveraging advanced analytical methods to turn ambiguous business challenges into high-impact, production-ready models, supported by robust data engineering practices.

Responsibilities
  • Lead Data Science Initiatives: Dive deep into complex and often nebulous requirements, applying expertise in areas such as time series forecasting and Natural Language Processing (NLP) to build, train, and maintain predictive models. Additionally, candidate should be capable of leading and mentoring more junior data scientists.
  • Problem Solver and Consultant: Engage in critical requirements gathering and data "sleuthing" (approximately 10-20% of the role) to connect business use cases with underlying data patterns. You will carve your own path to define and solve problems that lack clear initial definitions.
  • Deliver Automation and Insights: Partner with technical and non-technical groups to identify manual processes and provide recommendations for automation, including building models for functions like anomaly detection and case prediction.
  • Full-Lifecycle Ownership: Utilize data engineering skills to integrate and deploy your analytical solutions, ensuring scalability and operational reliability. This includes troubleshooting deployment issues as needed.
  • Collaborate and Communicate: Interface with internal teams and external client stakeholders to effectively communicate technical findings, maintain strong relationships, and ensure delivery aligns with overall objectives.
Minimum Qualifications
  • 5+ years of experience as a Data Scientist.
  • Bachelor of Science degree in a relevant field such as statistics, computer science, economics, mathematics, analytics, data science, business, or social sciences.
  • Proficiency in Python, including libraries for data analysis and modeling.
  • Strong SQL experience to facilitate deep dives and analysis of complex datasets.
  • Strong hands‑on experience with AWS services, Sagemaker, Lambda, Step Functions, Glue, S3, and Athena, used to build and manage production data pipelines.
  • Knowledge of CI/CD pipelines, version control (Git), and Infrastructure-as-Code.
  • Familiarity with logging, monitoring, and alerting using CloudWatch or similar tools.
  • Understanding of IAM roles, policies, and security best practices for AWS services.
  • Curiosity and a passion for exploring data to understand business context and connect technical work to real‑world impact.
  • Willingness to learn new tools/techniques.
Preferred Qualifications
  • Familiarity with AWS Cloud Development Kit (CDK) and/or Typescript.
  • Exceptional comfort with ambiguity and a proven ability to define and drive projects from vague concepts to concrete outcomes.
  • Strong consultative and communication skills, capable of representing the team effectively to clients.
  • Ability to work autonomously in a fully remote, flexible environment.
  • Advanced degree (MS or PhD) in statistics, computer science, data science, mathematics, analytics, engineering, or related fields; experience applying advanced statistical concepts including sampling considerations, bias detection, weighting techniques, handling missing or outlier data, exploratory analysis, and longitudinal forecasting; and understanding of the data analytics lifecycle (e.g., CRISP-DM).

Elder Research considers all qualified applicants for employment without regard to disability or veteran status or any other status protected under any federal, state, or local law or regulation.

If you need a reasonable accommodation to apply for a position with Elder Research, please email us at careers@elderresearch.com and provide your name and contact information.

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