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Data Operations Analyst Jobs (NOW HIRING)

Tempus

Sr. Data Operations Analyst

Chicago, IL · On-site

$88K - $111K/yr

As a Diagnostic Data Operations Analyst, you will serve as the technical data backbone of Tempus's diagnostics business unit. This role operates cross-functionally across Strategy & Operations ...

Aon Corporation

Data Operations Manager

Manhattan, NY · On-site

Provide timely technical support and data analysis for the Client Service team, including investigating data issues and preparing ad-hoc data cuts and reports. * Manage operational interactions with ...

Aon Corporation

Data Operations Manager

Manhattan, NY · Hybrid

Provide timely technical support and data analysis for the Client Service team, including investigating data issues and preparing ad-hoc data cuts and reports. * Manage operational interactions with ...

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Data Operations Analyst information

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$82.6K

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How much do data operations analyst jobs pay per year?

As of Jun 21, 2026, the average yearly pay for data operations analyst in the United States is $82,640.00, according to ZipRecruiter salary data. Most workers in this role earn between $62,500.00 and $97,000.00 per year, depending on experience, location, and employer.

What are Data Operations Analysts?

Data Operations Analysts are professionals who manage, optimize, and ensure the accuracy of data workflows within an organization. They are responsible for collecting, processing, and analyzing data to support business operations and decision-making. Their duties often include maintaining databases, troubleshooting data issues, and collaborating with other teams to improve data quality and efficiency. By ensuring data integrity and availability, Data Operations Analysts help organizations make data-driven decisions and streamline their operations.

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

To thrive as a Data Operations Analyst, you need strong analytical skills, proficiency in data management, and a relevant degree such as in computer science, statistics, or a related field. Familiarity with SQL, data visualization tools (such as Tableau or Power BI), and data pipeline systems is typically required, along with certifications like Microsoft Certified: Data Analyst Associate being advantageous. Attention to detail, problem-solving ability, and effective communication are essential soft skills for collaborating with cross-functional teams and ensuring data integrity. These skills and qualities are vital for maintaining accurate data flows, supporting business decisions, and driving operational efficiency.

How does a Data Operations Analyst typically collaborate with other departments to improve data processes?

Data Operations Analysts regularly work with cross-functional teams, including IT, business intelligence, and department leads, to streamline data collection, integration, and reporting. They often serve as the bridge between technical and non-technical teams, translating business needs into actionable data solutions. Effective collaboration may involve participating in meetings to understand project requirements, troubleshooting data issues with engineering teams, and training staff on new data tools or procedures. Strong communication skills are essential, as the role requires aligning diverse stakeholders toward common data integrity goals.

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

AspectData Operations AnalystData Analyst
Required CredentialsBachelor's in Data Science, IT, or related field; certifications like Microsoft Certified Data AnalystBachelor's in Statistics, Mathematics, or related field; certifications like Microsoft Certified Data Analyst
Work EnvironmentData teams, IT departments, business operationsBusiness units, marketing, finance, or research teams
Employer & Industry UsageTech companies, finance, healthcare, retailMarketing agencies, consulting firms, finance, healthcare

While both roles involve working with data, Data Operations Analysts focus on managing data workflows, ensuring data quality, and supporting data infrastructure. Data Analysts primarily analyze data to generate insights, reports, and support decision-making. The roles often overlap but differ in their core responsibilities and focus areas.

More about Data Operations Analyst jobs
What cities are hiring for Data Operations Analyst jobs? Cities with the most Data Operations Analyst job openings:
Who are the top companies hiring for Data Operations Analyst jobs? The top employers for Data Operations Analyst jobs are:
What states have the most Data Operations Analyst jobs? States with the most job openings for Data Operations Analyst jobs include:
What job categories do people searching Data Operations Analyst jobs look for? The top searched job categories for Data Operations Analyst jobs are:
Data Operations Analyst jobs near you
Infographic showing various Data Operations Analyst job openings in the United States as of June 2026, with employment types broken down into 89% Full Time, and 11% Part Time. Highlights an 81% Physical, 8% Hybrid, and 11% Remote job distribution, with an average salary of $82,640 per year, or $39.7 per hour.
Sr. Data Operations Analyst

Sr. Data Operations Analyst

Tempus

Chicago, IL • On-site

$88K - $111K/yr

Full-time

Posted 14 days ago

Job description

Passionate about precision medicine and advancing the healthcare industry?
Recent advancements in underlying technology have finally made it possible for AI to impact clinical care in a meaningful way. Tempus' proprietary platform connects an entire ecosystem of real-world evidence to deliver real-time, actionable insights to physicians, providing critical information about the right treatments for the right patients, at the right time.
As a Diagnostic Data Operations Analyst, you will serve as the technical data backbone of Tempus's diagnostics business unit. This role operates cross-functionally across Strategy & Operations, Business Intelligence, Commercial Systems, and AI Engineering - and has three core responsibilities: (1) developing and maintaining the data architecture that powers AI agents and cross-functional data products, (2) translating operational workflow requirements into technical specifications that Engineering and BI teams can execute against and (3) you will be the primary owner of dashboards and operational reports - responsible for building them, keeping them accurate, and ensuring they tell a clear story to leadership. Alongside that, you will define the data layer that makes agent building possible and partner cross-functionally to ensure data products are built on a stable, scalable foundation that supports both customer-facing and internal operations.
What You'll Do
  • Build and own the operational data architecture: Serve as the technical lead in translating diagnostic business needs into operational data processes. Define data models, source-to-target mappings, and the structural logic that connects SFDC, OPUS, LIMS, Hub, and lab systems into unified, reliable data products.
  • Operationalize diagnostic data pipelines: Utilize SQL and data transformation tools to create and combine operational workflow data streams - including order, case, communication, and physician activity data - into formats that power dashboards, agents, and downstream analytics.
  • Lead data architecture for AI agent development: Partner with AI Engineering and Tempus One agent teams to define the data requirements for diagnostic workflow agents (e.g., order status, tissue request automation, cancellation workflows). Translate operational needs into BRDs and technical specifications that engineering teams can build from.
  • Support GenAI and agent lifecycle management: Assist in scoping, piloting, and ongoing monitoring of AI agents for diagnostic workflows. Define success metrics, establish ground truth evaluation frameworks, and manage the feedback loop between operations and the AI team post-launch.
  • Build cross-functional data products: Extend operational reporting into shared data products used by BI, Commercial Systems, and business leadership. Ensure that data is structured, documented, and accessible enough to serve as input for agent builds, executive reporting, and cross-team analytics.
  • Continuously improve the data pipeline: Evaluate and enhance existing data processing logic, implement new data sources, monitor for data drift post-agent launch, and partner with BI and Engineering to resolve data quality and latency issues.
  • Own reporting and dashboard development: Design, build, and maintain core Looker dashboards and operational reports - including physician health, workflow performance, case volume, and KPI tracking. You are the primary builder and maintainer; leadership should be able to rely on these products as their source of truth. This includes identifying KPIs with leadership, validating data accuracy, and iterating on dashboards as business needs evolve.
  • Partner cross-functionally: Engage with Business Intelligence, Commercial Systems/SFDC, AI Engineering, Product, and Internal Operations teams to identify data gaps, align on architecture decisions, and ensure data products are built on a stable, scalable foundation across the diagnostics business.
Required Knowledge and Skills
  • Bachelor's degree in an analytical, computational, or healthcare-related field (e.g., Data Science, Bioinformatics, Computer Science, Biomedical Engineering, Public Health)
  • 4-6 years of relevant experience in data analytics, data engineering, healthcare analytics, or clinical operations data
  • Deep proficiency in SQL and experience with data transformation tools (e.g., dbt); ability to write and optimize complex queries across multi-source schemas
  • Experience with data visualization tools (Looker strongly preferred; Tableau acceptable)
  • Demonstrated experience building or operationalizing AI/ML data pipelines, agent workflows, or automated data products
  • Excellent interpersonal and communication skills; proven ability to translate technical data requirements to non-technical stakeholders and business leadership
  • Comfort with ambiguity, ability to create structure in fast-moving environments, and strong instinct for prioritization when data access is incomplete
  • Proficient in Google Suite (Sheets, Docs, Slides) and Excel
Nice to Haves
  • Experience in healthcare diagnostics, oncology, or life sciences
  • Familiarity with CRM systems (Salesforce/SFDC) and clinical data systems (EMR, LIMS)
  • Experience with prompt engineering, LLM agent testing, or AI agent evaluation frameworks

$80,000 - 116,000 - Hybrid (3 days in office at Tempus HQ in Chicago)
The expected salary range above is applicable if the role is performed from Illinois and may vary for other locations (California, Colorado, New York). Actual salary may vary based on qualifications and experience. Tempus offers a full range of benefits, which may include incentive compensation, restricted stock units, medical and other benefits depending on the position.
We are an equal opportunity employer. We do not discriminate on the basis of race, religion, color, national origin, gender, sexual orientation, age, marital status, veteran status, or disability status.

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