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Entry Level Ai Data Engineer Jobs in Colorado (NOW HIRING)

asrcfh

AI/ML Software Engineer

Colorado Springs, CO

We are seeking highly motivated Software Engineers to join our team as an AI Engineer at Schriever ... Experience working with sensitive data and adhering to data privacy regulations * Experience in ...

asrcfh

AI/ML Software Engineer

Colorado Springs, CO · On-site

We are seeking highly motivated Software Engineers to join our team as an AI Engineer at Schriever ... Experience working with sensitive data and adhering to data privacy regulations * Experience in ...

Garmin Ltd.

Data Scientist 1

Louisville, CO · On-site

$85 - $115/hr

Ensure data quality, governance, and compliance with data privacy and AI regulations Basic Qualifications * Bachelor's Degree in Computer Science, Electrical Engineering, Computer Engineering ...

New

Sierra Nevada Corporation

AI/ML Engineer II

Lone Tree, CO

$99K - $136K/yr

Identify data gaps and propose solutions to improve data quality. * Conduct performance testing and validation of AI/ML models using rigorous evaluation metrics. Optimize models for accuracy ...

Eliassen Group

Data Analyst

Almont, CO · On-site

$60 - $70/hr

Partner closely with Finance, Accounting, and Engineering to define requirements, translate ... All AI-assisted evaluations and responses are reviewed by human recruiters before any hiring ...

Sierra Nevada Corporation

AI/ML Engineer II

Lone Tree, CO · On-site

$99K - $136K/yr

Identify data gaps and propose solutions to improve data quality. * Conduct performance testing and validation of AI/ML models using rigorous evaluation metrics. Optimize models for accuracy ...

Pwc

US Tech - AI Engineering Senior Associate

Denver, CO · On-site

$55K - $187K/yr

Those in data science and machine learning engineering at PwC will focus on leveraging advanced ... PwC does not intend to hire experienced or entry level job seekers who will need, now or in the ...

CACI International, Inc.

AI/ML Engineer

Aurora, CO · On-site

AI/ML Engineer Job Category: Science Time Type: Full time Minimum Clearance Required to Start: TS ... Analyzing large multi-domain datasets such as images, text, and/or graph data to identify ...

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Entry Level Ai Data Engineer information

What are some common challenges faced by entry level AI data engineers in their first year on the job?

Entry level AI data engineers often encounter challenges such as learning to manage large datasets efficiently, understanding complex data pipelines, and adapting to rapidly evolving AI tools and frameworks. Collaborating with data scientists and senior engineers can be initially overwhelming, but it's a great opportunity to learn industry best practices. Balancing multiple tasks like data cleaning, preprocessing, and supporting model deployment while honing programming skills is typical. Proactively seeking feedback and asking questions is key to overcoming these hurdles and growing in the role.

What are the key skills and qualifications needed to thrive as an entry level AI data engineer, and why are they important?

To thrive as an Entry Level AI Data Engineer, you need proficiency in programming languages like Python or Java, a foundational understanding of data structures and algorithms, and a relevant degree in computer science or a related field. Familiarity with data processing frameworks (e.g., Hadoop, Spark), cloud platforms (e.g., AWS, Azure), and basic knowledge of machine learning libraries are typically expected. Strong analytical thinking, attention to detail, and effective teamwork set outstanding candidates apart. These skills and qualities are crucial for building reliable data pipelines, supporting AI models, and ensuring efficient collaboration within technical teams.

What is the difference between Entry Level Ai Data Engineer vs Data Analyst?

AspectEntry Level Ai Data EngineerData Analyst
Required SkillsBasic programming, data modeling, understanding of AI/ML conceptsData visualization, statistical analysis, SQL proficiency
CertificationsPython, SQL, entry-level AI/ML coursesExcel, Tableau, SQL certifications
Work EnvironmentTech companies, AI startups, data-driven teamsBusiness, marketing, finance sectors
Job FocusBuilding AI models, data pipelines, integrating AI solutionsInterpreting data, creating reports, supporting decision-making

While both roles involve working with data, Entry Level Ai Data Engineers focus on developing AI models and data infrastructure, whereas Data Analysts primarily analyze data to generate insights. The former requires some knowledge of AI/ML, while the latter emphasizes statistical and visualization skills.

Can you be an entry level AI data engineer with no experience?

Entry level AI data engineer roles typically require some foundational knowledge of programming, data management, and machine learning concepts, but many employers are open to candidates with limited experience if they demonstrate strong analytical skills and a willingness to learn. Gaining relevant skills through online courses, certifications, or internships can improve your chances of qualifying for such positions. Practical experience with tools like Python, SQL, and cloud platforms is often beneficial even at the entry level.

How to get into entry level AI data engineering?

To enter an entry-level AI data engineering role, develop skills in programming languages like Python and SQL, and gain experience with data processing tools such as Apache Spark or Hadoop. Building a strong foundation in databases, data modeling, and machine learning concepts, along with relevant certifications or coursework, can improve your chances of securing an entry-level position.

What is an entry level AI data engineer?

An Entry Level AI Data Engineer is a professional who helps build and maintain data pipelines and infrastructure to support artificial intelligence and machine learning applications. They typically work with large volumes of data, ensuring it is properly collected, cleaned, and organized for analysis. Their responsibilities may include working with databases, data processing tools, and cloud platforms, as well as collaborating with data scientists and software engineers to enable AI-driven solutions. This role is ideal for recent graduates or those new to the field, providing foundational experience in data engineering within the context of AI.
What are the most commonly searched types of Ai Data Engineer jobs in Colorado? The most popular types of Ai Data Engineer jobs in Colorado are:
What are popular job titles related to Entry Level Ai Data Engineer jobs in Colorado? For Entry Level Ai Data Engineer jobs in Colorado, the most frequently searched job titles are:
What job categories do people searching Entry Level Ai Data Engineer jobs in Colorado look for? The top searched job categories for Entry Level Ai Data Engineer jobs in Colorado are:
Entry Level Ai Data Engineer jobs near you
Infographic showing various Entry Level Ai Data Engineer job openings in Colorado as of August 2026, with employment types broken down into 1% As Needed, 82% Full Time, 13% Part Time, and 4% Contract. Highlights an 87% Physical, 3% Hybrid, and 10% Remote job distribution.

Data Engineer with AI/ML Framework - Denver, CO (In-Person Interview)

CA-One Tech Cloud Inc.

Denver, CO • On-site

$117K - $141K/yr

Other

Posted 13 days ago

Job description

Those who can do In-person interview with Client.

Primary Skill Expectations:- Strong in SQL, Spark , Good Communication.

Job Overview:
We are seeking a skilled professional with strong expertise in Python, Spark, and leading AI/ML frameworks to design and build scalable, intelligent data solutions. The ideal candidate will have hands-on experience with big data platforms and distributed data processing.

  • Design, develop, and maintain scalable ETL/ELT data pipelines using Apache Spark and SQL
  • Build and optimize batch and near real-time data processing workflows across large-scale datasets
  • Develop data ingestion, transformation, and data quality frameworks for enterprise data platforms
  • Work with Delta Lake, data lakes, and cloud-based big data environments to ensure reliable data processing
  • Perform data modeling, query tuning, and performance optimization for large datasets
  • Integrate data from multiple source systems, databases, and external platforms
  • Implement data validation, monitoring, and troubleshooting processes to ensure data integrity
  • Collaborate with business analysts, architects, and cross-functional teams to deliver data-driven solutions
  • Support data governance, security, and compliance requirements across the data ecosystem

Required Skills

  • Strong proficiency in Apache Spark (PySpark) and SQL
  • Extnsive experience developing and optimizing ETL/ELT pipelines
  • Strong understanding of distributed data processing concepts and Spark architecture
  • Experience working with relational and non-relational databases
  • Proficiency in data modeling, performance tuning, and query optimization
  • Experience with workflow orchestration and scheduling tools (e.g., Airflow, Control-M, Azure Data Factory, or similar)
  • Familiarity with cloud data platforms such as Azure, AWS, or Google Cloud
  • Strong problem-solving, analytical, and troubleshooting skills

Apply