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Junior Data Engineering Jobs in Oregon (NOW HIRING)

OR · Hybrid

... engineering teams. * Oversee and maintain the business glossary, data dictionary, and critical data ... Mentor and support junior Data Governance Analysts, providing coaching on tools, governance ...

OR · On-site

$114K - $137K/yr

Ability to guide junior engineers and contribute to technical design reviews. * Strong ... Experience in data quality initiatives such as Master Data Management (MDM). * Experience ...

AI Engineer

Portland, OR · On-site

$55K - $187K/yr

... junior team members in AI implementation and data engineering practices What You Must Have - At least a Bachelor's degree or, in lieu of a degree, demonstrating in addition to the minimum years of ...

You will guide and scale a high-performing group of Data Scientists and Engineers focused on US ... Mentor, grow, and empower senior and junior data scientists. Foster a culture of high autonomy ...

Mentor and develop technical competency of junior team members * Perform and/or lead necessary ... Working knowledge of AI prompt engineering and the effective application of generative AI ...

Sr Integration Engineer

Bend, OR · On-site

$120 - $150/hr

Stay current with industry trends, best practices, and emerging technologies in data engineering ... Mentoring (10%) * Guide junior members on product‑centric approaches and technical best practices.

New

$70K - $104K/yr

Responsibilities We are seeking a motivated and extremely detail-oriented Junior Python Programmer ... In this role, you will collaborate with a cross-functional team of developers, data scientists, and ...

BI Data Engineer

Springfield, OR · On-site +1

$52.75 - $68.50/hr

Mentor and develop technical competency of junior team members * Perform and/or lead necessary ... Working knowledge of AI prompt engineering and the effective application of generative AI ...

... engineers, platform engineers, data scientists and many more, enabling you to level up in true end ... Provide guidance to junior team members on model development and EDA * Work with Product Manager(s ...

Junior Software Engineer

OR · On-site +1

$82K - $106K/yr

We experiment to improve, actively seeking data to inform decisions and to assess our own ... This is a role for someone early in their engineering career who wants to do work that matters. No ...

Provide guidance and mentorship to junior team members, fostering a culture of continuous learning and improvement * Keep abreast of the latest trends and technologies in data engineering, healthcare ...

Our engineering team leverages emerging technologies and best practices across data security ... Mentor, motivate, and coach junior members on technical best practices and inspire professional ...

Senior Backend Software Engineer, ObservoAI

OR · Remote

$122K - $161K/yr

... engineering initiatives at scale for the Observo.ai team, our cutting-edge AI-driven data pipeline ... Provide technical leadership and mentorship to senior and junior engineers, driving system ...

Showing results 21-40

Junior Data Engineering information

See Oregon salary details

$35.4K

$75.9K

$115.8K

How much do junior data engineering jobs pay per year?

As of Aug 7, 2026, the average yearly pay for junior data engineering in Oregon is $75,912.00, according to ZipRecruiter salary data. Most workers in this role earn between $51,300.00 and $84,600.00 per year, depending on experience, location, and employer.

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 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 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 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 are the most commonly searched types of Data Engineering jobs in Oregon? The most popular types of Data Engineering jobs in Oregon are:
What job categories do people searching Junior Data Engineering jobs in Oregon look for? The top searched job categories for Junior Data Engineering jobs in Oregon are:
What cities in Oregon are hiring for Junior Data Engineering jobs? Cities in Oregon with the most Junior Data Engineering job openings:
Infographic showing various Junior Data Engineering job openings in Oregon as of August 2026, with employment types broken down into 1% As Needed, 70% Full Time, 26% Part Time, and 3% Contract. Highlights an 87% Physical, 3% Hybrid, and 10% Remote job distribution, with an average salary of $75,912 per year, or $36.5 per hour.

Lead AI and Data Solution Engineer

U.S. Financial Technology

On-site, Remote

$200K - $215K/yr

Full-time

Medical, Retirement, PTO

Re-posted yesterday


Job description

OVERVIEW

The Company

U.S. Financial Technology (U.S. FinTech) is seeking an experienced Lead AI and Data Solution Engineer to drive the development, integration, and deployment of advanced AI, data engineering, and cloud-based solutions. This is a full-time remote opportunity. 

U.S. FinTech built and operates the largest and most advanced mortgage securitization platform in the world, supporting the Uniform Mortgage-Backed Security (UMBS) of Fannie Mae and Freddie Mac.

Supporting 70% of the mortgage-backed securities in the market, U.S. FinTech provides best-in-class single-family issuance, bond administration, disclosure, and tax services. We support a broad portfolio of products for our clients with full lifecycle management.

Our market-leading, cloud-based, end-to-end platform executes transactions on an extraordinary scale which has bolstered liquidity in the secondary mortgage market, one of the largest and most important financial markets in the world. Our unique approach to securitization combines the best minds in financial services with the know-how, flexibility, and innovation of leading technologists.

RESPONSIBILITIES

Job Information

The ideal candidate will have deep expertise in data engineering, agentic AI systems, large language models (LLMs), and Model Context Protocol (MCP). The preferred candidate will bring deep experience with AWS and Snowflake services, including a strong understanding of security best practices for cloud-based AI and data solutions. This role requires a hands-on leader who can design and code scalable, secure, and innovative data pipelines and AI solutions that deliver business value. 

Key Job Functions

  • Solution Engineering: Lead the design, development, and deployment of enterprise-scale data and AI solutions, ensuring alignment with business objectives and technical best practices. 
  • LLM and Agentic AI: Architect, implement, and optimize large language models and agentic AI workflows for business automation and decision support. 
  • Framework Expertise: Design and deploy AI solutions using leading frameworks such as LangChain, LangGraph, and n8n for scalable agent orchestration, workflow automation, and integration with business systems 
  • Model Context Protocol (MCP): Develop, integrate, and manage MCP-based solutions to enhance model interpretability, context management, and deployment at scale. 
  • Cloud and Data Engineering: Leverage AWS and Snowflake to build scalable, secure, and efficient data pipelines for structured and unstructured data. 
  • Collaboration: Partner with cross-functional teams, including other technology, business, risk, legal, and compliance stakeholders, to deliver integrated solutions. 
  • Innovation: Stay current with emerging technologies and industry trends in AI, data engineering, and cloud computing, driving continuous improvement and innovation. 
  • Governance and Compliance: Ensure all solutions meet regulatory, security, and compliance requirements relevant to the financial services industry. 
  • Mentorship: Provide technical leadership and mentorship to junior team members. 
QUALIFICATIONS

Education   

  • Bachelor's or Master's degree in Computer Science, Data Science, Engineering, or a related field. 

Minimum Experience  

  • 8+ years of experience in data engineering, AI solution development, or related roles. 
  • Proven expertise in large language models (LLMs), agentic AI systems, and Model Context Protocol (MCP). 
  • Good working experience developing and integrating AI solutions using AWS Bedrock, including prompt engineering, RAG, and enterprise application integration.
  • Hands-on experience building AI applications using Python frameworks such as LangChain, LlamaIndex, FastAPI, and AWS/OpenAI SDKs.
  • Strong experience with Snowflake and AWS services (Glue, S3, Lambda, SageMaker, etc.).
  • Experience in the financial services or mortgage industry is preferred.
  • Applicants must be authorized to work in the US without requiring employer sponsorship currently or in the future. U.S. FinTech does not offer sponsorship for this position.

Specialized Knowledge & Skills     

  • Deep understanding of AI/ML frameworks, data pipelines, and cloud-native architectures. 
  • Hands-on experience with LLM deployment, fine-tuning, and integration. 
  • Advanced proficiency in Python programming with the ability to design, develop, test, and troubleshoot production-grade AI/ML applications and reusable frameworks.
  • Proficiency in agentic AI design patterns and implementation. 
  • Expertise in Model Context Protocol (MCP) for context-aware model deployment and management. 
  • Strong knowledge of Snowflake, AWS, and advanced data modeling. 
  • Experience with data governance, security, and compliance best practices. 
  • Excellent communication, collaboration, and presentation skills. 
  • Ability to translate complex technical concepts for non-technical stakeholders. 

Pay Range $200,000 to $215,000

U.S. FinTech's pay range for this job level is a general guideline only and not a guarantee of compensation or salary. Additional factors considered in extending an offer include (but are not limited to) a candidate's qualifications, skills, competencies, and experience, as well as internal equity, alignment with market data, applicable bargaining agreement (if any), or other law. U.S. FinTech offers a competitive total compensation package, which includes a performance bonus, 401k match, healthcare coverage, PTO, and a broad range of other benefits.

Employment

As a condition of employment with U.S. Financial Technology, any successful job applicant will be required to  successfully complete a background investigation, which may also include a credit check for positions in some areas of our business.   

U.S. Financial Technology is an Equal Opportunity Employer.

##LI-Remote

Employment Type: FULL_TIME