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Junior Data Engineering Jobs in Colorado (NOW HIRING)

We're looking for dynamic Junior Data Analysts to join our mission! Learn more about us here ... Monitoring overall system and data health and raising any concerns with developers. * Suggest and ...

Senior Data Engineer, Global

Denver, CO · On-site

$109K - $148K/yr

Provide technical leadership and mentorship to junior data engineers, promoting engineering standards and best practices. * Participate in architecture discussions, code reviews, and platform design ...

... Junior Data Analyst to support enterprise data quality, analytics operations, and data pipeline governance efforts. This role will partner closely with Data Engineers, BI Developers, Data Scientists ...

Principal Data Engineer

Denver, CO · On-site

$210K - $290K/yr

... data engineering technical excellence through code reviews, reusable frameworks, documentation, knowledge sharing, and mentoring other data engineers * Mentor Junior and Senior Data Engineers and ...

Principal Data Engineer

Denver, CO · On-site

$210K - $290K/yr

... data engineering technical excellence through code reviews, reusable frameworks, documentation, knowledge sharing, and mentoring other data engineers * Mentor Junior and Senior Data Engineers and ...

New

... engineering principles, data modeling, and data analysis. * Strong problem-solving, troubleshooting, communication, and cross-functional collaboration skills. * Demonstrated ability to mentor junior ...

... engineering principles, data modeling, and data analysis. * Strong problem-solving, troubleshooting, communication, and cross-functional collaboration skills. * Demonstrated ability to mentor junior ...

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Junior Data Engineering information

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 Colorado?

The most popular types of Data Engineering jobs in Colorado are:

What are popular job titles related to Junior Data Engineering jobs in Colorado?

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

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

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

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

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

Infographic showing various Junior Data Engineering job openings in Colorado as of August 2026, with employment types broken down into 1% As Needed, 85% Full Time, 11% Part Time, 1% Temporary, and 2% Contract. Highlights an 85% Physical, 4% Hybrid, and 11% Remote job distribution.

MLOps & Data Engineer

Highlands Ranch, CO • On-site

Sierra Nevada Corporation
Guided Missile and Space Vehicle Manufacturing • 5 - 10K employees

$112K - $135K/yr

Other

Medical, Dental, Vision, Life, Retirement, PTO

Posted 10 days ago


Sierra Nevada Corporation rating

8.7

Company rating: 8.7 out of 10

Based on 29 frontline employees who took The Breakroom Quiz


Job description

Are you looking to leverage your technical creativity? Dream, Innovate, Inspire and Empower the next generation to transform humanity through technology and imagination! As a Data Engineer II, you will oversee the development and optimization of complex data pipelines and transformations. You will collaborate with cross-functional teams to ensure the efficient and secure integration, management, and utilization of data within the Enterprise Data Warehouse (EDW). Your role will also involve mentoring junior data engineers and implementing best practices. As SNC's corporate team, we provide the company and its business areas with strategic direction and business support spanning executive management, finance and accounting, operations, human resources, legal, IT, information security, facilities, marketing, and communications.

Responsibilities
  • Oversee the design and development of data pipelines and transformations that feed AI and ML systems across the platform
  • Collaborate with the AI/LLM Platform team and other engineering teams to understand data and model requirements and ensure effective solutions
  • Mentor and guide junior data engineers
  • Develop and enforce best practices for data engineering processes
  • Implement advanced data integration, data management, and data quality solutions, including experiment tracking and model registry systems
  • Perform testing, debugging, and optimization of data pipelines and model serving infrastructure
  • Ensure data security and compliance with CMMC and SNC data governance standards
  • Develop and maintain comprehensive documentation for data processes
  • Design and operate feature stores and model serving infrastructure supporting real-time and batch inference
  • Manage graph and relational data stores supporting AI applications such as knowledge graphs and entity resolution
  • Monitor data pipeline and model serving health, participating in on-call rotation for data infrastructure
Qualifications You Must Have
  • Bachelor’s degree in Computer Science, Data Engineering, or a related field
  • 2+ years of experience in data engineering or a related role
  • Higher level relevant degree may substitute for experience
  • Relevant experience can be considered as a substitute for the required educational qualifications
  • In the absence of a degree, a minimum of 6 years of related experience is required
  • Proficiency in SQL and experience with ETL/orchestration tools such as Airflow, dbt, or Prefect
  • Experience with cloud platforms such as AWS, Azure, or Google Cloud
  • Strong problem-solving and analytical skills
  • Working SQL knowledge and experience working with relational databases
  • Experience with AWS cloud services: S3, Redshift, Glue
  • Experience building data pipelines, architectures, and data sets
  • Experience performing root cause analysis on data to answer specific business questions or issues
  • Strong Python skills, with experience in data engineering frameworks such as Spark, dbt, Airflow, or Prefect
  • Operational responsibilities (schedules, monitoring, logging, alerting, error handling, etc.)
  • Exposure to ML lifecycle tools such as MLflow, Weights & Biases, or Kubeflow
Qualifications We Prefer
  • Experience building data pipelines, architectures, and data sets
  • Experience performing root cause analysis on data to answer specific business questions or issues
  • Experience with AWS cloud services (e.g., S3, EC2, RDS, Redshift, Glue, Lambda, Step Functions, Athena, CloudWatch, ECS, IAM)
  • Experience with object-oriented scripting languages and frameworks (e.g., Python, Java)
  • Familiarity with source system integration patterns (e.g., SQL, APIs)
  • Exposure to operational responsibilities (schedules, monitoring, logging, alerting, error handling, etc.)
  • Basic understanding of Master Data Management (MDM) concepts and exposure to MDM solutions
  • Familiarity with DevOps practices and tools, with some hands‑on experience in a CI/CD environment
  • Experience with big data technologies (e.g., Hadoop, Spark)
  • Certifications in data engineering or related fields
Essential Functions
  • Ability to work on a computer for extended periods
  • Frequent communication with team members and stakeholders
  • Ability to work in an office or hybrid environment
  • Occasional travel may be required
  • Must be able to lift up to 10 lbs occasionally
  • Ability to ensure data engineering practices adhere to industry-specific regulations and security standards (e.g., ITAR, DFARS, NIST), safeguarding sensitive data throughout the data lifecycle
  • Experience with ML lifecycle tools such as MLflow, Weights & Biases, or Kubeflow
  • Familiarity with feature store platforms (Feast, Tecton, Hopsworks)
  • Experience with graph databases (Neo4j, Amazon Neptune) supporting knowledge graphs or entity resolution
  • Familiarity with vector databases or retrieval-augmented generation (RAG) pipelines (Pinecone, Weaviate, pgvector)
  • Experience with Kubernetes for deploying data or ML workloads
  • Familiarity with data observability tools (Monte Carlo, Great Expectations)

This posting will be open for application for a minimum of 5 days and may be extended based on business needs.

Estimated Starting Salary Range: $108,496.89 - $149,183.22. Compensation varies depending on a wide array of factors, such as candidates' key skills, relevant work experience, and education/training/certifications. The disclosed range estimate may be adjusted for any applicable geographic differential associated with the location at which the position may be filled.

SNC offers a generous benefit package, including medical, dental, and vision plans, 401(k) with 150% match up to 6%, life insurance, 3 weeks paid time off, tuition reimbursement, and more.

IMPORTANT NOTICE: To conform to U.S. Government international trade regulations, applicant must be a U.S. Citizen, lawful permanent resident of the U.S., protected individual as defined by 8 U.S.C. 1324b(a)(3), or eligible to obtain the required authorizations from the U.S. Department of State or U.S. Department of Commerce. Learn more about the background check process for Security Clearances.

SNC is a global leader in aerospace and national security committed to moving the American Dream forward. We’re known and respected for our mission and execution focus, agility, and disruptive and rapid innovation. We provide leading edge technologies and transformative solutions that support our nation’s most critical security needs. If you are mission-focused, thrive in collaborative environments, and want to make our country stronger with state‑the‑art technologies that safeguard freedom, join our team! SNC is an Equal Opportunity Employer committed to an environment free of discrimination. Employment decisions are made based on merit without regard to race, color, age, religion, sex, national origin, disability, status as a protected veteran or other characteristics protected by law. SNC is a trusted global leader in aerospace and national security. Our innovative solutions enable connected protection through command, control and communications systems, as well as ISR, cyber, electromagnetic spectrum management, and other high capabilities for systems across all domains – sea, land, air, space and cyber. As a longstanding leader in defense technology, SNC is the optimum intersection of commercial, defense and non‑traditional contractors. We are one of the only privately owned mid-tier A&D contractors and we pride ourselves on our ability to invest early and often to ensure mission success on or ahead of schedule. It’s part of our mission to always stay one step ahead; working on solutions today to solve the problems of tomorrow. Founded in 1963, SNC is owned by Chairwoman Eren Ozmen and CEO Fatih Ozmen.

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