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Manager Data Operations Lead Jobs (NOW HIRING)

Lead, ML Data Operations

San Francisco, CA · On-site

$241K - $382K/yr

About the Role We're looking for a Lead of ML Data Operations to build and lead a new function at ... Source, evaluate, and manage relationships with external data labeling vendors, from initial ...

Scale and manage data and onboarding operations to streamline customer lifecycle end-to-end * Own and lead data analysis projects, and generate the insights that help drive customer conversations ...

Data Operations

San Francisco, CA · On-site

$250K - $350K/yr

Manage multiple projects against research and model timelines and adjust quickly as priorities change. Skills and Qualifications Minimum Qualifications: * Experience owning operational, data, product ...

Description SAIC is seeking a highly skilled TS/SCI Cleared Data Operations Technical Lead to design, manage, and deliver the foundational data infrastructure critical to transforming Special ...

Data Operations Engineer

Fort George G Meade, MD · On-site

$127K - $152K/yr

* Lead a technically focused Data Operations team responsible for reliability, uptime, and speed-to ... Manage expectations, communicate technical roadmaps, and translate mission-specific data needs into ...

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Manager Data Operations Lead information

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$31K

$97.1K

$172K

How much do manager data operations lead jobs pay per year?

As of Sep 10, 2026, the average yearly pay for manager data operations lead in the United States is $97,145.00, according to ZipRecruiter salary data. Most workers in this role earn between $66,000.00 and $125,500.00 per year, depending on experience, location, and employer.

What does a manager data operations lead do?

A Manager Data Operations Lead oversees the daily operations related to data management within an organization. This role is responsible for ensuring data integrity, optimizing data workflows, and leading a team of data professionals. Key responsibilities include implementing data governance policies, coordinating with IT and business units, and ensuring compliance with data security standards. The role requires strong leadership, technical expertise, and excellent problem-solving skills.

How does a manager data operations lead collaborate with cross-functional teams to ensure data quality and consistency?

A Manager Data Operations Lead frequently works with teams such as engineering, analytics, and business stakeholders to align data processes and standards. They facilitate communication between departments to clarify data requirements, resolve discrepancies, and implement best practices for data governance. Regular meetings and progress check-ins are typical, helping to quickly address issues and maintain high data quality across all business units. Effective collaboration ensures that data remains a reliable resource for decision-making and strategic initiatives.

What are the key skills and qualifications needed to thrive as a manager data operations lead, and why are they important?

To thrive as a Manager Data Operations Lead, you need a solid background in data management, analytics, and process optimization, typically with a degree in computer science, information systems, or a related field. Experience with data warehousing tools, ETL systems, SQL, and platforms like Snowflake or AWS, along with certifications such as PMP or Six Sigma, is highly valuable. Strong leadership, communication, and problem-solving skills enable you to coordinate teams, manage stakeholders, and drive continuous improvement. These skills are crucial for ensuring data quality, operational efficiency, and the strategic alignment of data initiatives within an organization.

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

AspectManager Data Operations LeadData Analyst
Required CredentialsBachelor's degree in Data Science, Business, or related field; experience in data managementBachelor's degree in Statistics, Data Science, or related field; proficiency in data analysis tools
Work EnvironmentLeads data teams, manages data operations, collaborates with multiple departmentsAnalyzes data sets, creates reports, supports decision-making
Employer & Industry UsageUsed in corporate, tech, finance sectors for managing data teamsCommon across industries for data insights and reporting
Search & Comparison IntentOften compared for leadership roles in data managementCompared for technical data analysis skills

The Manager Data Operations Lead focuses on overseeing data management teams and ensuring data quality across organizations, while Data Analysts primarily analyze data sets to generate insights. Both roles require strong data skills, but the manager role emphasizes leadership and operational oversight.

More about Manager Data Operations Lead jobs

What cities are hiring for Manager Data Operations Lead jobs?

Cities with the most Manager Data Operations Lead job openings:

What are the most commonly searched types of Data Operations Lead jobs?

The most popular types of Data Operations Lead jobs are:

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For Manager Data Operations Lead jobs, the most frequently searched job titles are:

Infographic showing various Manager Data Operations Lead job openings in the United States as of September 2026, with employment types broken down into 1% As Needed, 79% Full Time, 17% Part Time, 1% Temporary, 1% Contract, and 1% Nights. Highlights an 93% Physical, 2% Hybrid, and 5% Remote job distribution, with an average salary of $97,145 per year, or $46.7 per hour.

Manager Data Operations & Annotations, Autonomy Data

Ann Arbor, MI

$150K - $180K/yr

Full-time

Medical, Dental, Vision, PTO

Posted 9 days ago


Key responsibilities

  • Lead the organization and end-to-end operations that collect, annotate, validate, and deliver high-quality real-world data for ML and autonomy development.

  • Partner with ML and autonomy teams to translate model needs into data requirements, collection strategies, and operational priorities.

  • Design and improve annotation, validation, and quality-control workflows using tooling, automation, and metrics to optimize quality, coverage, speed, and cost.


Job description

About Zipline

Zipline is the world's largest and most experienced drone delivery service. We are on a mission to serve all humans equally by ensuring access to food, medicine and essential goods anytime, anywhere. We design, build, and operate the world's largest autonomous logistics system, delivering critical supplies quickly and reliably. Today, Zipline operates on four continents, makes a delivery somewhere in the world every 30 seconds, and has completed millions of deliveries to date, including blood, vaccines, medical supplies, food, and retail products. 

Our customers include the world's largest and most prominent healthcare systems, governments, retailers, restaurants and global businesses who rely on us to save lives, reduce emissions, increase economic opportunity, and provide delivery from point A to point B as fast as possible. The drone is only 15% of what we've built to enable seamless, reliable, global operations.

Our system strengthens supply chains, reduces congestion, and gives people time back. With more than 140 million commercial autonomous miles safely flown, Zipline is redefining access to healthcare, consumer products, and food across the globe.

We operate at a global scale and are looking for practical problem solvers who thrive on real-world challenges and rapid growth. Our team is motivated by building systems that have a direct, meaningful impact on people's lives and by scaling the future of logistics. We are seeking people who sculpt from first principles, enjoy facing adversity, and can do the impossible at record breaking speeds.

About You and the Role

You will lead the team responsible for turning real-world data into high-quality, cost-effective datasets for Zipline's machine learning and autonomy teams.

This role spans field operations, autonomy, ML, engineering, and data infrastructure. You will set the strategy for how data is collected, annotated, and validated, while building an operation that continuously improves its quality, coverage, speed, and economics.

You will also lead and develop the organization behind these systems, while partnering closely with technical teams to ensure data operations evolve with the needs of our autonomy stack.

What You'll Do
  • Lead the organization and end-to-end operations that collect, annotate, validate, and deliver high-quality real-world data at the scale, speed, and cost required for ML and autonomy development.

  • Partner with ML and autonomy teams to translate model needs into data requirements, collection strategies, and operational priorities.

  • Design and improve annotation, validation, and quality-control workflows, using tooling, automation, and metrics to optimize quality, coverage, speed, and cost.

  • Develop managers and teams, establish clear ownership, and build a culture of accountability and continuous improvement.

  • Lead cross-functional programs and drive decisions across operations, engineering, ML, and autonomy.

  • Use operational data and feedback to identify bottlenecks and drive automation or engineering improvements that increase scale without proportional growth in manual effort or cost.

What You'll Bring
  • Experience leading and scaling operational or technical teams, including developing managers.

  • Experience owning technically complex operational systems and improving their performance at scale.

  • Strong systems thinking and technical judgment across people, process, hardware, software, and infrastructure.

  • Experience leading ambiguous, cross-functional work from problem definition through sustained operation.

  • Strong judgment in balancing quality, throughput, cost, and reliability.

  • A track record of using metrics, tooling, and automation to drive measurable operational improvements.

  • Clear communication and the ability to drive alignment and decisions across technical and operational teams.

What Will Make You Stand Out
  • Experience designing or operating large-scale data labeling or annotation programs.

  • Experience managing external vendors or distributed workforces supporting data operations.

  • Experience with machine learning, autonomy, robotics, aerospace, or other sensor-rich physical systems.

  • Familiarity with the ML data lifecycle, including data collection, sampling, annotation, validation, dataset generation, and model feedback loops.

  • Experience translating model performance gaps into targeted real-world data collection.

  • Familiarity with multimodal datasets, sensor data, telemetry, or logging systems.

What Success Looks Like

The right data reaches ML teams faster, at higher quality and lower cost. Data collection becomes increasingly deliberate, annotation and processing scale efficiently, and model needs translate quickly into action in the field. Ultimately, you will own a critical part of how Zipline learns from the real world.

What Else You Need To Know

The starting cash range for this role is $150,000 - $180,000. Please note that this is a target, starting cash range for a candidate who meets the minimum qualifications for this role. The final cash pay for this role will depend on a variety of factors, including a specific candidate's experience, qualifications, skills, working location, and projected impact. The total compensation package for this role may also include: equity compensation; overtime pay; discretionary annual or performance bonuses; sales incentives; benefits such as medical, dental and vision insurance; paid time off; and more. 

Zipline is an equal opportunity employer and prohibits discrimination and harassment of any type without regard to race, color, religion, age, sex, national origin, disability status, genetics, protected veteran status, sexual orientation, gender identity or expression, or any other characteristic protected by federal, state or local laws or our own sensibilities.

We value diversity at Zipline and welcome applications from those who are traditionally underrepresented in tech. If you like the sound of this position but are not sure if you are the perfect fit, please apply!

Voluntary Self-Identification

For government reporting purposes, we ask candidates to respond to the below self-identification survey. Completion of the form is entirely voluntary. Whatever your decision, it will not be considered in the hiring process or thereafter. Any information that you do provide will be recorded and maintained in a confidential file.

As set forth in Zipline 's Equal Employment Opportunity policy, we do not discriminate on the basis of any protected group status under any applicable law.