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Data Operations Director Jobs in Colorado (NOW HIRING)

... Director, Data Collective to lead the team that owns Sovrn's data platform end-to-end: the ... Own the operational posture of the data platform: SLOs, on-call health, incident response, and ...

Coordinate Data & BI capabilities to ensure operational KPIs are captured, measured, and actioned ... Partner with the Growth Director and Integration enterprise function during the 120-day integration ...

Revenue Operations Director

Westminster, CO · On-site +1

$105K - $145K/yr

Our impact is tangible, from connected machines that save fuel to data-driven insights that reduce ... Operations, RevOps, Director of Revenue, ASC 606, Revenue Recognition, Oracle, Salesforce, RevPro ...

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Data Operations Director information

See Colorado salary details

$54.7K

$135.1K

$210.3K

How much do data operations director jobs pay per year?

As of Aug 12, 2026, the average yearly pay for data operations director in Colorado is $135,147.00, according to ZipRecruiter salary data. Most workers in this role earn between $98,800.00 and $171,900.00 per year, depending on experience, location, and employer.

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

To thrive as a Data Operations Director, you need expertise in data management, analytics, process optimization, and a relevant degree such as in computer science, statistics, or information systems. Familiarity with data warehousing solutions, ETL tools, cloud platforms (like AWS or Azure), and certifications such as Certified Data Management Professional (CDMP) are commonly required. Leadership, strategic thinking, and strong communication skills are essential for driving cross-functional teams and aligning data initiatives with business goals. These capabilities ensure efficient, secure, and high-quality data operations that support informed decision-making and organizational growth.

How does a Data Operations Director typically collaborate with cross-functional teams to ensure data integrity and accessibility?

A Data Operations Director works closely with IT, data engineering, analytics, and business units to establish robust data governance practices and streamline data workflows. They often lead efforts to standardize data definitions, enforce quality controls, and implement access protocols to ensure that stakeholders across the organization can use reliable data for decision-making. Regular meetings, project management tools, and clear communication channels are essential for aligning priorities and resolving data-related issues efficiently. This cross-functional collaboration is key to maintaining high data integrity and fostering a data-driven culture.

What does a Data Operations Director do?

A Data Operations Director is responsible for overseeing the management, organization, and optimization of a company's data-related processes and teams. They ensure data quality, security, and accessibility, while aligning data management with business goals. This role often involves supervising data analysts, engineers, and other professionals, and implementing strategies for data governance and compliance. The Data Operations Director also collaborates with other departments to support data-driven decision making and operational efficiency.

What is the difference between Data Operations Director vs Data Analyst?

AspectData Operations DirectorData Analyst
Required CredentialsBachelor's or Master's in Data Science, Business, or related field; experience in data managementBachelor's in Data Science, Statistics, or related field; proficiency in data analysis tools
Work EnvironmentLeadership role overseeing data teams, strategic planningAnalyzing data sets, generating reports, supporting decision-making
Employer & Industry UsageUsed in organizations with large data operations, tech, finance, healthcareCommon across various industries for data insights and reporting

The Data Operations Director focuses on managing data teams and strategic data initiatives, while the Data Analyst concentrates on analyzing data to generate insights. Both roles require strong data skills, but differ in scope and responsibilities.

What are the most commonly searched types of Data Operations jobs in Colorado? The most popular types of Data Operations jobs in Colorado are:
What are popular job titles related to Data Operations Director jobs in Colorado? For Data Operations Director jobs in Colorado, the most frequently searched job titles are:
What cities in Colorado are hiring for Data Operations Director jobs? Cities in Colorado with the most Data Operations Director job openings:
Infographic showing various Data Operations Director job openings in Colorado as of August 2026, with employment types broken down into 100% Full Time. Highlights an 70% In-person, 10% Hybrid, and 20% Remote job distribution, with an average salary of $135,147 per year, or $65 per hour.

Director, Data Collective

Sovrn

Boulder, CO • On-site

Full-time

Medical, Dental, Vision, Life, Retirement, PTO

Re-posted 7 days ago


Job description

About Sovrn

Every interesting company solves important problems for other people.  Sovrn is a Software and Data business that helps Open Web businesses be and remain independent.  We help them understand their business better, operate more efficiently, and make & keep more money.

  • We believe in the freedom and free-flow of information.
  • We believe the Open Web is the largest source of this information.
  • We believe in helping Open Web businesses be and remain Independent.

Through Software products and Data solutions we help our customers:

  • Understand their business better, so they can make better decisions
  • Operate their business more efficiently, so they can invest in what matters most
  • Make (and Keep) more money, so they control their own destiny
About the Role

We're looking for a Director, Data Collective to lead the team that owns Sovrn's data platform end-to-end: the pipelines, lakehouse, data services, and cloud infrastructure that power our exchange, our products, and our customers' decisions. This is a hands-on engineering leadership role. You'll own team composition and hiring; lead architecture and design across the platform; and remain close enough to the code, the systems, and the tradeoffs to make real technical decisions, not just approve them.

You'll be working with a strong senior team, a modern stack, and an organization that already uses LLMs and agentic tooling across the data stack. We're looking for a leader who can take what's working from "in use" to "intentional practice." Someone with strong opinions about what high-leverage AI-native data engineering looks like at exchange scale, and the credibility to bring the rest of the org along.

Languages / components / tools in our stack: Python, Redpanda/Kafka, Databricks/Spark, AWS/S3, Terraform, Datadog, GitHub

What you'll be doing:

Team Leadership & Composition

  • Own the skill mix of the Data Collective team; lead hiring and performance management for engineers ranging from mid-level to Principal
  • Set the technical and cultural standards for the team: what "great" looks like in design, code review, on-call, and cross-team partnership
  • Mentor and grow engineers across levels through hands-on design collaboration, technical coaching, and clear career frameworks
  • Partner with the broader engineering leadership team on org-wide planning, budgeting, and roadmap tradeoffs; represent the team's work and constraints to executives

Data Platform Architecture & Engineering

  • Drive architectural decisions across pipeline design, data modeling, lakehouse architecture, and data services layers
  • Heavily contribute to the design and architecture of Sovrn's data pipelines, lakehouse, and data services: high-throughput streaming, always-on batch, petabyte-scale storage and query
  • Lead design reviews and set technical standards across the team; raise the bar on engineering rigor, observability, and operational excellence
  • Stay close enough to the systems to make real tradeoffs on performance, cost, governance, and reliability, and to know when the team's estimates and risk assessments are right

AI & Modern Data Engineering Practice

  • Set the team's direction on AI-native data engineering: where LLMs, RAG, agentic workflows, and AI-assisted tooling create real leverage in a high-throughput adtech environment, and where they don't
  • Establish standards for how the team evaluates, trusts, and operates AI-powered systems in production: observability, fallback behavior, model governance, and cost control
  • Identify high-leverage AI applications in the data stack: intelligent pipeline optimization, anomaly detection, automated data quality, forecasting, and LLM-powered data services

Operational Excellence & Cost Management

  • Own the operational posture of the data platform: SLOs, on-call health, incident response, and continuous improvement
  • Own the infrastructure cost footprint of the Data Collective across AWS and Databricks; drive structural cost improvements through architecture, and disciplined commitment management
  • Drive Infrastructure as Code (IaC) adoption, policy-as-code, governance frameworks (RBAC/ABAC, IAM, SCIM), and CI/CD for infrastructure across the team
  • Make sure the team is investing in the right balance of new capability, platform health, and tech debt

Cross-functional Collaboration

  • Provide domain expertise across the organization to enable business growth through data services and data models
  • Partner with Product, Data Science, AI/ML, Platform, and Security teams to ship end-to-end and to make Sovrn's data assets easier and safer to use
  • Serve as a senior point of counsel to all consumers and stakeholders of Sovrn's data: internal teams, leadership, and external customers of our Data-as-a-Service products
  • Communicate clearly at multiple levels: from architecture documents and design reviews to executive updates on cost, capacity, and risk
A successful candidate will have:
  • 10+ years of software / data engineering experience, with a strong hands-on track record in data platforms, distributed systems, or backend infrastructure
  • 4+ years leading and growing engineering teams, including hiring, leveling, and performance management of senior and principal-level engineers
  • Deep, current technical proficiency. You still read code, write design docs, and lead architecture, not just review work
  • Hands-on experience in big data and distributed data processing in the AWS ecosystem (Python, Spark, Kafka/Redpanda, Databricks or similar lakehouse platforms)
  • Experience operating data systems at scale: real-time streaming, batch pipelines, data lakes, metadata management, lineage, and governance
  • Working knowledge of cloud platform engineering practices: IaC (Terraform), CI/CD, observability, IAM, and cost management
  • Track record of leading or substantially contributing to AI / agentic engineering efforts in production, not just experimentation, but shipped, operated, and iterated on
  • Hands-on experience operating production vector databases at scale, including the pipelines and infrastructure to refresh hundreds of millions of vectors on a daily cadence
  • Familiarity with adtech data infrastructure (SSP, DSP, exchange, or ad server environments) and the programmatic ecosystem (OpenRTB, bid request/response flows, auction mechanics, supply path optimization) is a strong plus
  • Experience with data security and compliance (PII, CCPA, GDPR)
  • Ability to clearly communicate architectural concepts and team strategy at multiple levels, from engineers to executives to the board
  • Comfort driving technical and organizational decisions in ambiguous, fast-moving environments

We understand that no candidate is perfectly qualified for any job. Experience comes in different forms, many skills are transferable, and passion goes a long way. Even more important than your resume is a clear demonstration of accountability and the ability to thrive in a fluid and collaborative environment. We expect you to learn new things in this role and encourage you to apply if your experience is close to what we're looking for.

Location: Sovrn offices are located in Boulder, CO and New York, NY. We believe collaboration and shared purpose lead to deeper relationships, more creative problem-solving, and more learning, faster. For employees located near one of our offices, working in-person is our default. We trust people to use personal agency when focused work or life circumstances call for flexibility.. #LI-Hybrid

Application Deadline: Priority deadline July 1, 2026. Applications will be accepted on a rolling basis thereafter until the position is filled.

Compensation and Benefits: The base salary for this position is $225,000 to $250,000 annually. Actual base salary will depend on the candidate's education, experience, skills, and location. In addition to salary, the total compensation package includes bonus and equity. Sovrn offers a full slate of benefits from medical, dental, and vision coverage, short and long-term disability, life insurance, paid parental leave, 401(k) plan and match, 11 paid holidays, flexible vacation, and commuter benefits.

How to Apply: Submit your application through https://www.sovrn.com/careers/. If you require a reasonable accommodation to participate in any part of the application or interview process, please contact peopleops@sovrn.com.

Equal Opportunity Employer: Sovrn is proud to be an Equal Opportunity Employer and provides equal employment opportunities to all employees and applicants regardless of race, color, religion, gender, gender identity, age, national origin, disability, parental or pregnancy status, marriage and civil partnership, sexual orientation, veteran status, or any other characteristic protected by law. Reasonable accommodations will be made to meet the requirements of the Americans with Disabilities Act.

Recruitment Agencies: Sovrn does not accept agency resumes. Please do not forward resumes to our jobs alias or Sovrn employees. Sovrn is not responsible for any fees related to unsolicited resumes.