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Data Ops Manager Jobs in Colorado (NOW HIRING)

AI Ops Engineer III

Denver, CO · On-site

$54.25 - $74.25/hr

Collaborate with data scientists, analysts, and business stakeholders to interpret requirements and ... Develop and manage cloud infrastructure as code using Terraform to ensure reliable deployments

Lead Data Engineer

Englewood, CO · On-site

$101K - $133K/yr

... manage data integration solutions to support analytics/reporting needs. - Conduct complete ... ML Ops, AI/ML, Data Warehousing, Spark, Python, Scala/Java, SQL, Big Data tools, statistical ...

LLM Ops Engineer

Denver, CO · On-site

$105 - $130/hr

... sensitive data, and enforcing governance standards.* Create a consistent developer experience ... Experience deploying, managing, and scaling models across multiple AI providers such as OpenAI ...

Operations Management - Ops Coordinator, Work Order Coordinator, Ops Management, Planners, Safety ... For more information about how JLL processes your personal data, please view our Candidate Privacy ...

Data Infrastructure Management: * Designs, builds, tests, and maintains databases, data lakes, and ... Experience with Microsoft Fabric, Microsoft Power BI, Azure Dev Ops, Microsoft Visual Studio.

Data Engineer I

Rifle, CO · On-site

$80K - $110K/yr

Data Infrastructure Management: * Designs, builds, tests, and maintains databases, data lakes, and ... Experience with Microsoft Fabric, Microsoft Power BI, Azure Dev Ops, Microsoft Visual Studio.

Senior ML Ops Engineer

Denver, CO · On-site

$123K - $170K/yr

... management. · Build and support containerized ML workloads and deployment workflows using ... What You Need to Succeed: · Bachelor's degree in Computer Science, Data Science, Artificial ...

AI Ops Engineer II

Denver, CO · On-site

$100K - $137K/yr

Title: AI Ops Engineer II Duration: 4-month contract Location: Denver, CO, 80202(Remote ... Familiarity with broader I&O data, including ITSM platforms (ServiceNow for ticketing/CMDB) and ...

Showing results 21-40

Data Ops Manager information

What is a Data Ops manager?

Data Ops Managers are professionals responsible for overseeing the processes, tools, and teams involved in managing and optimizing data operations within an organization. They ensure the smooth flow, quality, and accessibility of data across various platforms and departments. Their role often includes automating data pipelines, implementing data governance practices, and collaborating with data engineers, analysts, and business stakeholders to support data-driven decision making.

What are some common challenges faced by a Data Ops manager, and how can they be addressed?

Data Ops Managers often encounter challenges such as coordinating across multiple teams, ensuring data quality, and managing fast-evolving data pipelines. Success in this role requires strong communication skills to align stakeholders, robust processes for monitoring data workflows, and the ability to quickly troubleshoot issues when data delivery is disrupted. Adopting automation tools and fostering a culture of continuous improvement can help Data Ops Managers maintain reliable, scalable systems while supporting organizational data needs.

What are the key skills and qualifications needed to thrive as a Data Ops manager, and why are they important?

To excel as a Data Ops Manager, you need a deep understanding of data management, analytics workflows, and process automation, often supported by a degree in computer science or a related field. Familiarity with tools like SQL, Python, cloud platforms (AWS, Azure), and orchestration systems such as Apache Airflow is typically required, along with certifications in data management or cloud services. Strong leadership, problem-solving, and communication skills help coordinate cross-functional teams and drive data initiatives. These competencies are crucial for ensuring data reliability, optimizing data pipelines, and enabling data-driven decision-making across the organization.

What is the difference between Data Ops Manager vs Data Engineer?

AspectData Ops ManagerData Engineer
Primary FocusOversees data operations, workflows, and process optimizationBuilds, constructs, and maintains data pipelines and infrastructure
Required SkillsData management, process improvement, team coordinationProgramming, database systems, ETL development
CertificationsData management, cloud certifications often preferredSQL, cloud platform certifications, programming languages
Work EnvironmentCollaborates with data teams, operations, and business unitsWorks closely with data scientists, analysts, and developers

While both roles involve working with data, the Data Ops Manager focuses on managing data workflows and operational efficiency, whereas the Data Engineer concentrates on building and maintaining data infrastructure. Understanding these differences helps in choosing the right career path or hiring the appropriate professional for your data needs.

What are popular job titles related to Data Ops Manager jobs in Colorado?

For Data Ops Manager jobs in Colorado, the most frequently searched job titles are:

Infographic showing various Data Ops Manager job openings in Colorado as of August 2026, with employment types broken down into 87% Full Time, 11% Part Time, 1% Temporary, and 1% Contract. Highlights an 81% Physical, 2% Hybrid, and 17% Remote job distribution.

Full-time

Re-posted 4 days ago


Job description

About the Team

Launched in 2021, Fanatics Betting and Gaming is the online and retail sports betting subsidiary of Fanatics, a global digital sports platform. The Fanatics Sportsbook is available to 95% of the addressable online sports bettor market in the U.S. Fanatics Casino is currently available online in Michigan, New Jersey, Pennsylvania and West Virginia. Fanatics Betting and Gaming operates twenty-two retail sports betting locations, including the only sportsbook inside an NFL stadium at Northwest Stadium. Fanatics Betting and Gaming is headquartered in New York with offices in Denver, Leeds and Dublin.

Overview

As an Operations Data Analyst at Fanatics Betting & Gaming, you are on the front lines of how the Operations Department understands its own performance. You sit within the Analytics & AI Enablement team and own the data pipelines, reporting, and analytical work that CX, Fraud, Payments, WFM, and VIP leaders rely on to make decisions every day.

This is not a passive reporting role. You are expected to take ownership across multiple operational areas, building and maintaining the data layer, surfacing insights, and flagging risks before they become crises. You work closely within the Strategy & Analytics team to ensure our data is accurate, scalable, and directly connected to Ops top-line goals.

We are actively building toward an AI-first way of operating, and this role is part of that. The ideal candidate is technically sharp, relentlessly detail-oriented, and genuinely curious, both about what the data is saying and about how AI can change the way we find and act on answers. You are comfortable moving fast, owning ambiguous problems, and holding yourself to a high bar without being told to.

Responsibilities

Analytical Work & Insights

  • Respond to high-priority analytical requests from Ops leaders - turning raw data into clear, actionable insights on a tight timeline.
  • Proactively surface trends, anomalies, and risks from the data without waiting to be asked.
  • Support scenario analysis and impact sizing for product initiatives, operational changes, and staffing decisions.
  • Own the development and maintenance of dashboards and reports that give operational leaders clear visibility into performance across CX, Fraud, Payments, WFM, and VIP.
  • Ensure all reporting reflects up-to-date data, clearly defined KPIs, and documented assumptions.
  • Present findings and data narratives directly to operational stakeholders - translating complexity into clear recommendations they can act on.

Data Infrastructure & Pipelines

  • Build, maintain, and improve data pipelines that feed Ops reporting and dashboards - ensuring consistent, accurate, and well-documented data flows.
  • Partner with Data Engineering on DBT development, data store buildout, and pipeline reliability.
  • Proactively identify and resolve data quality issues; escalate blockers that require cross-functional resolution.
  • Deprecate manual, one-off data pulls and replace with automated, always-on solutions.
  • Build alerting infrastructure on critical Ops metrics to catch issues early and reduce reactive firefighting.

AI Enablement & Innovation

  • Support the AI agent roadmap by contributing data, analytical rigor, and validated data foundations before an agent moves to build.
  • Track and report on AI agent performance post-deployment - measuring impact against top-line Ops goals.
  • Actively look for opportunities to apply AI to your own workflow - whether that's speeding up analysis, improving accuracy, or eliminating manual work.
  • Bring a point of view on where AI can and can't be trusted, and flag where human judgment needs to stay in the loop.
Required Qualifications
  • 2+ years of experience in an analytical role - business intelligence, data analytics, strategic operations, or a related field.
  • Strong hands-on SQL experience; ability to write, QA, and optimize complex queries independently.
  • Experience supporting AI/ML workflows, agent builds, or automation initiatives in an analytical capacity.
  • Experience building and maintaining dashboards in Sigma, Tableau, or a comparable data visualization tool.
  • Familiarity with DBT or similar data transformation frameworks.
  • High attention to detail - you catch data quality issues before they surface in leadership reporting.
  • Strong communication skills; able to translate analytical findings into plain language for operational stakeholders.
  • Comfortable operating in fast-paced, ambiguous environments with shifting priorities.
Preferred Qualifications
  • Familiarity with operational KPIs across customer support, fraud, payments, or workforce management.
  • Experience with Python or similar scripting languages for data manipulation and automation.
  • Experience in gaming, fintech, sports, or other operationally intensive, high-volume environments.
  • Bachelor's degree in Analytics, Computer Science, Statistics, Economics, or a related field.

Depending on the role, your interview and onboarding experience may include in-person components, such as onsite interviews or Launching into Better: LIVE-a multi-day cultural immersion in New York City for full-time, non-seasonal hires. These sessions are designed to build connection and bring our culture to life, though specific travel and participation requirements will be confirmed based on your role and location. Your recruiter will provide clear guidance at each stage of the process.

For information about our benefits, please visit https://benefitsatfanatics.com/