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Remote Dataops Engineer Jobs in Colorado (NOW HIRING)

Releady

Data Engineer, Consultant

Denver, CO · On-site +1

$140K - $160K/yr

Hybrid or Remote, however must reside in the following states: WA, OH, CA, AZ, CO, CT, FL, GA, MD ... Proven experience implementing CI/CD pipelines, Infrastructure as Code, and DataOps practices.

Releady

Data Engineer, Principal

Denver, CO · On-site +1

$170K - $190K/yr

Hybrid or Remote, however must reside in the following states: WA, OH, CA, AZ, CO, CT, FL, GA, MD ... Champion and apply DevOps and DataOps best practices, including CI/CD, automated testing ...

All JobsDataops Engineer JobsRemote Dataops Engineer JobsRemote Dataops Engineer Jobs in Colorado

Remote Dataops Engineer information

What is the difference between Remote Dataops Engineer vs Data Engineer?

AspectRemote Dataops EngineerData Engineer
CredentialsBS in CS, Data Science, or related; certifications like AWS, GCP, or AzureSimilar credentials; often with additional database or software engineering certifications
Work EnvironmentRemote or hybrid, collaborative teams, cloud platformsRemote or on-site, data-focused teams, cloud and on-prem infrastructure
Industry UsageTech, finance, healthcare, e-commerceTech, finance, retail, telecom
Search & Comparison IntentUnderstanding roles in data operations, cloud deployment, automationFocus on data pipeline development, database management, ETL processes

The Remote Dataops Engineer and Data Engineer roles share many credentials and work environments, often overlapping in cloud and data infrastructure. However, Data Engineers typically focus more on building and maintaining data pipelines and databases, while Dataops Engineers emphasize automating deployment, monitoring, and optimizing data workflows in cloud environments.

What is a Remote DataOps Engineer?

A Remote DataOps Engineer is a technology professional who works remotely to manage, automate, and optimize data pipelines and processes within an organization. Their main goal is to streamline the flow of data between various systems, ensuring the availability, quality, and security of data for analytics and business operations. They collaborate closely with data engineers, analysts, and IT teams to develop efficient workflows, automate repetitive tasks, and monitor data infrastructure performance. By working remotely, they leverage cloud-based tools and communication platforms to support distributed teams and global data operations.

How do Remote DataOps Engineers typically collaborate with cross-functional teams to ensure smooth data pipeline operations?

Remote DataOps Engineers often work closely with data engineers, analysts, and DevOps teams using collaboration tools like Slack, Jira, and GitHub. Regular virtual meetings and documentation are essential to align on pipeline requirements, monitor data quality, and resolve issues quickly. Clear communication and proactive status updates help build trust with stakeholders and ensure that data infrastructure supports business needs efficiently, even when working remotely.

What are the key skills and qualifications needed to thrive as a Remote DataOps Engineer, and why are they important?

To thrive as a Remote DataOps Engineer, you need expertise in data engineering, automation, and pipeline management, typically backed by a degree in computer science or a related field. Familiarity with tools like Apache Airflow, Kubernetes, CI/CD systems, and cloud platforms such as AWS or Azure is highly valued, along with relevant certifications. Excellent problem-solving, communication, and collaboration skills are crucial for managing distributed teams and complex data workflows. These skills and qualities ensure efficient, reliable, and scalable data infrastructure essential for modern data-driven organizations.
What are the most commonly searched types of Dataops Engineer jobs in Colorado? The most popular types of Dataops Engineer jobs in Colorado are:
What are popular job titles related to Remote Dataops Engineer jobs in Colorado? For Remote Dataops Engineer jobs in Colorado, the most frequently searched job titles are:
What job categories do people searching Remote Dataops Engineer jobs in Colorado look for? The top searched job categories for Remote Dataops Engineer jobs in Colorado are:
What cities in Colorado are hiring for Remote Dataops Engineer jobs? Cities in Colorado with the most Remote Dataops Engineer job openings:
Remote Dataops Engineer jobs near you

Data Engineer, Consultant

Releady

Denver, CO • On-site, Remote

$140K - $160K/yr

Contractor

Posted 7 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.