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Data Engineer Ml Jobs in Colorado (NOW HIRING)

Data Engineer, Consultant

Denver, CO · On-site +1

$140K - $160K/yr

AI Enablement & Stakeholder Communication Support integration of AI/ML-ready datasets by ensuring ... of data engineering experience. Advanced hands-on expertise in SQL, including automation and ...

Data Engineer - Snowflake Specialist

Denver, CO · On-site

$117K - $141K/yr

... ML, Software Development, Technical Writing, and Digital Transformation. We partner with top ... Senior Operations & Data Engineer (Snowflake Specialist) / Cloud Engineer Location: Colorado ...

Data Engineer - & GC

Denver, CO · On-site

$117K - $141K/yr

Role: Data Engineer Location: Denver, CO - 4 days per week work from Client office Please find ... We are seeking a skilled professional with strong expertise in Python, Spark, and leading AI/ML ...

Data Engineer, Principal

Denver, CO · On-site

$117.10 - $130.87/hr

Engineer robust ELT/ETL solutions that ingest, process, and curate structured and semi-structured ... Experience supporting enterprise AI/ML, advanced analytics, and data product ecosystems.

Data Engineer I-II

Brighton, CO · On-site

$97K - $127K/yr

Maintain working knowledge of Databricks' AI/ML tooling and broader industry trends, applying that ... Data Engineer I, II, and III. Positions in this series are flexibly staffed; placement and ...

Data Engineer I-II

Brighton, CO · Hybrid

$124K - $149K/yr

Maintain working knowledge of Databricks' AI/ML tooling and broader industry trends, applying that ... Data Engineer I, II, and III. Positions in this series are flexibly staffed; placement and ...

Senior Data Engineer

Denver, CO · On-site

$170K - $220K/yr

As a Sr. Data Engineer on our data team, you will be building out the core data asset that ... Work closely with our data science team to run ML models on top of billions of data points * Build ...

Role Summary As a Lead Platform Data Engineer, you will own the data architecture that connects ... AI/ML Integration: Previous experience building feature stores or pipelines specifically designed ...

Senior ML Ops Engineer

Denver, CO · On-site

$123K - $170K/yr

What You Need to Succeed: · Bachelor's degree in Computer Science, Data Science, Artificial ... in Python programming, ML Framework and Agentic AI. Implemented model monitoring, experiment ...

Senior Data Engineer - Databricks

Denver, CO · On-site

$117K - $141K/yr

You will work closely with ML engineers, product teams, and the Enterprise Architecture team to ensure the data backbone behind Sugar Predict is always fast, clean, and ready to deliver at a global ...

Senior Data Engineer

Aurora, CO

$108K - $146K/yr

Build and deploy AI/ML models leveraging modern frameworks * Work with large datasets using platforms like Delta Lake and other big data technologies * Manage and integrate multiple databases for ...

Senior Data Engineer

Aurora, CO · On-site

$108K - $146K/yr

We are seeking a skilled professional with strong expertise in SQL, Python, Spark, and leading AI/ML frameworks to design and build scalable, intelligent data solutions. The ideal candidate will have ...

Showing results 21-40

Data Engineer Ml information

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

To thrive as a Data Engineer ML, you need strong programming skills (especially in Python or Scala), knowledge of data modeling, and a solid foundation in database technologies, typically supported by a degree in computer science or a related field. Familiarity with big data frameworks (like Spark or Hadoop), cloud platforms (AWS, GCP, or Azure), and ETL tools, as well as relevant certifications, is highly beneficial. Excellent problem-solving abilities, teamwork, and clear communication help you collaborate with data scientists and stakeholders effectively. These skills are essential for building robust data pipelines and infrastructure that enable scalable, high-quality machine learning solutions.

What does a data engineer ML do?

A Data Engineer ML (Machine Learning) is responsible for designing, building, and maintaining the data pipelines and infrastructure necessary for machine learning applications. They clean, process, and organize large datasets to ensure data quality and accessibility for data scientists and ML engineers. In addition, they may work on deploying machine learning models to production environments and optimizing data workflows for efficiency and scalability.

What is the difference between Data Engineer Ml vs Data Scientist?

AspectData Engineer MlData Scientist
Required CredentialsBachelor's in CS, Data Engineering certificationsBachelor's/Master's in CS, Data Science certifications
Work EnvironmentBuilding data pipelines, managing databasesAnalyzing data, creating models
Employer & Industry UsageTech companies, finance, healthcareResearch institutions, tech firms, finance

Data Engineer Ml focuses on developing and maintaining data infrastructure and pipelines, while Data Scientists analyze data and build predictive models. Both roles often collaborate but serve different functions within data teams.

How do data engineer ML roles typically collaborate with data scientists and machine learning engineers on projects?

Data Engineer ML professionals work closely with data scientists and machine learning engineers by building and maintaining robust data pipelines, ensuring clean and reliable datasets are readily available for modeling and analysis. They often participate in meetings to understand model requirements, help optimize data storage for performance, and support the deployment of machine learning models into production environments. Effective collaboration involves continuous communication to troubleshoot data issues, implement data validation, and scale solutions as project needs evolve. This teamwork ensures that data-driven projects move efficiently from experimentation to deployment.
What are popular job titles related to Data Engineer Ml jobs in Colorado? For Data Engineer Ml jobs in Colorado, the most frequently searched job titles are:
What cities in Colorado are hiring for Data Engineer Ml jobs? Cities in Colorado with the most Data Engineer Ml job openings:
Infographic showing various Data Engineer Ml job openings in Colorado as of August 2026, with employment types broken down into 1% As Needed, 84% Full Time, 12% Part Time, and 3% Contract. Highlights an 86% Physical, 4% Hybrid, and 10% Remote job distribution.

Data Engineer, Consultant

Releady

Denver, CO • On-site, Remote

$140K - $160K/yr

Contractor

Posted 21 days ago


Job description

OVERVIEW

Releady is partnering with a leading healthcare technology company to hire a Data Engineer, Consultant for its Data Services team. This organization provides the technology backbone and shared data infrastructure for nonprofit, community, and regional health plans nationwide, unifying clinical, claims, demographic, and provider data into a single governed platform that powers automation and AI deployment across core health plan operations.

This role is a senior individual contributor and technical leader who reports to a Senior Manager or Manager within Data Solutions and drives end-to-end delivery of complex data engineering solutions across cloud data platforms. The Consultant partners closely with Solution Design Leads, Architects, Product Managers, and business stakeholders to translate solution designs and business requirements into scalable, secure, production-ready data products, and provides technical leadership and mentorship without formal people management responsibility.

NOTE: *Must be eligible to work on W2 without sponsorship. Not eligible for C2C.

  • Pay Rate: $70–$80/hr
  • Duration: 6-month contract-to-hire
  • Location: Hybrid or Remote, however must reside in the following states: WA, OH, CA, AZ, CO, CT, FL, GA, MD, MN, NV, OR, AL, IL, VA, WI, TX, NY
RESPONSIBILITIES

Solution Architecture & Delivery

Lead the design and implementation of complex data pipelines and data products from development through production.

Translate solution designs and business requirements into detailed technical architecture and implementation plans.

Architect and build scalable, secure, and highly available data solutions across enterprise data platforms.

Apply advanced data modeling techniques, including Data Vault 2.0, dimensional, and domain-oriented models, to support analytics and reporting needs.

Quality, Security & Operational Excellence

Embed data quality, testing, security, and observability by design across data pipelines.

Drive operational excellence, including incident analysis, stabilization, performance tuning, and deployment optimization.

Identify and implement optimization opportunities related to performance, reliability, and cloud cost management.

Technical Leadership & Standards

Influence and evolve the data engineering standards, patterns, and frameworks used by delivery teams.

Provide technical leadership and mentorship to Data Engineers and Senior Data Engineers through design reviews and code reviews.

Work within an agile / DevSecOps pod model, collaborating closely with solution leads, data modelers, analysts, and business partners.

AI Enablement & Stakeholder Communication

Support integration of AI/ML-ready datasets by ensuring data is well-modeled, reliable, and governed.

Communicate complex technical concepts clearly to both technical and non-technical stakeholders.

QUALIFICATIONS

Bachelor's degree or equivalent experience, with a minimum of seven years of data engineering experience.

Advanced hands-on expertise in SQL, including automation and pipeline optimization.

Strong experience with cloud platforms, Azure preferred, and services such as ADLS, Synapse, and Data Factory.

Extensive experience with modern data platforms including Snowflake and Databricks, and orchestration tools such as Airflow or Tidal.

Deep understanding of data modeling, integration patterns, data architecture, data quality, and data warehousing.

Proven experience implementing CI/CD pipelines, Infrastructure as Code, and DataOps practices.

Strong understanding of security, privacy, and compliance requirements in regulated environments.

Experience working with large-scale, distributed data platforms and parallel processing architecture.

Experience with Airflow or Tidal (migrating from Tidal; comparable orchestration tools considered)

Excellent communication and stakeholder engagement skills, with a proven ability to lead technically without formal people management responsibility.

Healthcare industry experience is preferred, including exposure to Epic or similar ecosystems.

We are an equal opportunity employer and value diversity at our company. We do not discriminate on the basis of race, religion, color, national origin, gender, sexual orientation, age, marital status, veteran status, disability status, or other non-merit factor. We are committed to creating a diverse and inclusive environment for all employees.