Data Operations Manager Jobs
Data Operations Manager jobs are open across healthcare, fintech, logistics, and retail, from mid-level analyst leads to senior director, with specializations in pipeline management, data quality, and business intelligence operations. Find a role that fits from the openings below and apply directly.
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Our Mission
Reflection’s mission is to build open superintelligence and make it accessible to all. We’re developing open weight models for individuals, agents, enterprises, and even nation states. Our team of AI researchers and company builders come from DeepMind, OpenAI, Google Brain, Meta, Character.AI, Anthropic and beyond.
Role Overview
Data is playing an increasingly crucial role at the frontier of AI innovation. Many of the most meaningful advances in recent years have come not from new architectures, but from better data. In this role, the data operations you build will directly shape how our models perform on critical capabilities — agentic tool use, long-horizon reasoning and robust safety alignment. You'll work with world-class researchers advancing the frontier while building the operational infrastructure to scale these efforts.
What You’ll Do
- Develop a deep understanding of Reflection’s research, product and business roadmap and derive from these the data needs and sourcing strategies.
- Work closely with researchers to understand nuanced technical requirements, define quality bars, then orchestrate partnerships and data pipelines that meet them.
- Lead cross-functional efforts to maximize research velocity without compromising in the quality of data partnerships.
- Manage these partnerships including evaluating suppliers, negotiating agreements, and verifying deliverables.
- Develop deep knowledge of the broader data ecosystem to identify gaps and opportunities to innovate at the frontier.
- Combine the technical depth to understand what makes high-quality training data with the operational excellence to deliver it.
- Anticipate and resolve bottlenecks, risks and inefficiencies across data operations to maximize throughput and impact.
What We’re Looking For
- 6+ years of experience in business operations, strategy, venture capital, private equity or consulting. We will also consider high-trajectory candidates with fewer years of experience and an exceptional track record – often former startup founders.
- Have owned large ambiguous problems end-to-end and can break them down into clear actionable plans.
- Are comfortable engaging senior leaders, influencing decisions and driving alignment across teams.
- Thrive in fast-moving, high-pressure environments, bringing resourcefulness, adaptability and ideally a sense of humor to pair with the sense of urgency.
- Are highly analytical with strong intuition for what are the important questions, rigorous in investigating and clear in communicating insights to decision-makers.
- Can operate at all levels from discussing strategy and vision with leadership, to troubleshooting issues with individual contributors and external partners.
- Communicate clearly and collaborate effectively across technical and non-technical domains.
- Have experience with data analysis tools such as SQL, Python, Tableau, Excel or similar.
- Are genuinely curious about LLM training, and care deeply about the impact of AI on business, research and society.
Bonus Points
- A technical background such as a computer science degree and/or experience in engineering, product, data science or AI.
- Direct experience with data collection, labeling, or annotation for machine learning / AI systems.
- Worked with research teams at AI companies or research-oriented organizations.
- A track record of managing large numbers of diverse vendors and external contractors.
- A consulting background, with experience translating complex requirements into concrete deliverables.
What We Offer
We believe that to build superintelligence that is truly open, you need to start at the foundation. Joining Reflection means building from the ground up as part of a small talent-dense team. You will help define our future as a company, and help define the frontier of open foundational models. We want you to do the most impactful work of your career with the confidence that you and the people you care about most are supported.
- Top-tier compensation: Salary and equity structured to recognize and retain the best talent globally.
- Health & wellness: Comprehensive medical, dental, vision, life, and disability insurance.
- Life & family: Fully paid parental leave for all new parents, including adoptive and surrogate journeys. Financial support for family planning.
- Benefits & balance: paid time off when you need it, relocation support, and more perks that optimize your time.
- Opportunities to connect with teammates: lunch and dinner are provided daily. We have regular off-sites and team celebrations.
Our Mission
Reflection’s mission is to build open superintelligence and make it accessible to all. We’re developing open weight models for individuals, agents, enterprises, and even nation states. Our team of AI researchers and company builders come from DeepMind, OpenAI, Google Brain, Meta, Character.AI, Anthropic and beyond.
Role Overview
Data is playing an increasingly crucial role at the frontier of AI innovation. Many of the most meaningful advances in recent years have come not from new architectures, but from better data. In this role, the data operations you build will directly shape how our models perform on critical capabilities — agentic tool use, long-horizon reasoning and robust safety alignment. You'll work with world-class researchers advancing the frontier while building the operational infrastructure to scale these efforts.
What You’ll Do
- Develop a deep understanding of Reflection’s research, product and business roadmap and derive from these the data needs and sourcing strategies.
- Work closely with researchers to understand nuanced technical requirements, define quality bars, then orchestrate partnerships and data pipelines that meet them.
- Lead cross-functional efforts to maximize research velocity without compromising in the quality of data partnerships.
- Manage these partnerships including evaluating suppliers, negotiating agreements, and verifying deliverables.
- Develop deep knowledge of the broader data ecosystem to identify gaps and opportunities to innovate at the frontier.
- Combine the technical depth to understand what makes high-quality training data with the operational excellence to deliver it.
- Anticipate and resolve bottlenecks, risks and inefficiencies across data operations to maximize throughput and impact.
What We’re Looking For
- 6+ years of experience in business operations, strategy, venture capital, private equity or consulting. We will also consider high-trajectory candidates with fewer years of experience and an exceptional track record – often former startup founders.
- Have owned large ambiguous problems end-to-end and can break them down into clear actionable plans.
- Are comfortable engaging senior leaders, influencing decisions and driving alignment across teams.
- Thrive in fast-moving, high-pressure environments, bringing resourcefulness, adaptability and ideally a sense of humor to pair with the sense of urgency.
- Are highly analytical with strong intuition for what are the important questions, rigorous in investigating and clear in communicating insights to decision-makers.
- Can operate at all levels from discussing strategy and vision with leadership, to troubleshooting issues with individual contributors and external partners.
- Communicate clearly and collaborate effectively across technical and non-technical domains.
- Have experience with data analysis tools such as SQL, Python, Tableau, Excel or similar.
- Are genuinely curious about LLM training, and care deeply about the impact of AI on business, research and society.
Bonus Points
- A technical background such as a computer science degree and/or experience in engineering, product, data science or AI.
- Direct experience with data collection, labeling, or annotation for machine learning / AI systems.
- Worked with research teams at AI companies or research-oriented organizations.
- A track record of managing large numbers of diverse vendors and external contractors.
- A consulting background, with experience translating complex requirements into concrete deliverables.
What We Offer
We believe that to build superintelligence that is truly open, you need to start at the foundation. Joining Reflection means building from the ground up as part of a small talent-dense team. You will help define our future as a company, and help define the frontier of open foundational models. We want you to do the most impactful work of your career with the confidence that you and the people you care about most are supported.
- Top-tier compensation: Salary and equity structured to recognize and retain the best talent globally.
- Health & wellness: Comprehensive medical, dental, vision, life, and disability insurance.
- Life & family: Fully paid parental leave for all new parents, including adoptive and surrogate journeys. Financial support for family planning.
- Benefits & balance: paid time off when you need it, relocation support, and more perks that optimize your time.
- Opportunities to connect with teammates: lunch and dinner are provided daily. We have regular off-sites and team celebrations.
See All 395+ Data Operations Manager Jobs
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Find Data Operations Manager JobsData Operations Manager Job Market
A snapshot from current openings nationwide, updated as new roles post.
Who's Hiring
- Amazon28
- Google22
- Oracle15
- Crunchbase14
- Apple9
Top Industries Hiring
- Technology & Software135
- Consulting & Professional Services28
- Biotechnology & Pharmaceuticals16
- Electronics & Hardware16
- Banking & Financial Services15
What Employers Look For
The qualifications that appear most often in data operations manager jobs.
- 5+ years of experience in data engineering, analytics, or data operations roles
- Proficiency in SQL and at least one scripting language such as Python
- Hands-on experience with pipeline orchestration tools like Airflow, dbt, or Prefect
- Experience with cloud data platforms including Snowflake, BigQuery, or Redshift
- Bachelor's degree in computer science, information systems, or a related field
- Familiarity with data governance frameworks and data quality monitoring practices
Tips for Your Data Operations Manager Job Search
Quantify pipeline and quality outcomes
Your resume needs to show scale and results, not just responsibilities. Replace 'managed data pipelines' with the volume of records processed, error rates reduced, or SLA improvements you delivered. Hiring managers for this role scan for operational impact first.
Highlight your toolstack by stack tier
Group your tools by layer: ingestion, transformation, orchestration, and monitoring. Listing dbt, Airflow, or Fivetran alongside SQL and Python tells a technical hiring manager exactly where you sit in the data stack and which team you'll work closest with.
Target openings by data maturity stage
A data operations manager role at a Series B startup means building from scratch. The same title at a Fortune 500 means governance and scale. Filter openings by company size and funding stage so your experience actually matches what the team needs.
Apply early to roles that fit
Migrate Mate lists data operations manager openings from across the United States in one place, so you can find roles that match and apply directly to each listing.
Prepare for a technical operations case interview
Many hiring processes for this role include a scenario where you diagnose a broken pipeline, a data quality incident, or a team workflow bottleneck. Practice walking through root cause analysis out loud, not just identifying the problem but prioritizing the fix under a time constraint.
Negotiate with incident and uptime data
When you reach the offer stage, ground your compensation ask in operational outcomes you've owned. Reduced downtime, improved data freshness, or faster mean-time-to-resolution on incidents are measurable contributions that support a stronger number than seniority alone.
Data Operations Manager Jobs: Frequently Asked Questions
Which companies are hiring the most data operations managers?
The companies hiring the most data operations managers right now include Amazon, Google, and Oracle, with the largest share of openings in California, Texas, and New York, based on current listings on Migrate Mate as of June 2026. Demand is especially strong in healthcare systems, fintech platforms, and large-scale logistics companies that rely on high-volume, time-sensitive data operations.
How many data operations manager jobs are remote?
About 38% of data operations manager openings are fully remote or hybrid as of June 2026, reflecting strong employer flexibility for this role. Sub-areas with the highest remote share include data quality oversight, pipeline monitoring, and analytics engineering coordination, where day-to-day work is tool-driven rather than on-site dependent.
How do you become a data operations manager?
Most data operations managers move up from individual contributor roles in data engineering, analytics, or business intelligence. Build depth in pipeline tooling and data quality practices first, then take on cross-functional projects that require coordinating between engineering and analytics teams. Demonstrating ownership over reliability metrics and team workflows is what typically triggers a promotion or lateral move into management.
Can you get a data operations manager job with limited experience?
Getting hired with limited experience is possible if you can show ownership over a specific operational outcome, even in a smaller scope. Build a portfolio project that demonstrates end-to-end pipeline management, including monitoring and incident response. Roles at early-stage companies or those titled 'lead' or 'associate manager' are more likely to consider candidates transitioning from senior individual contributor positions.
What does the data operations manager interview process look like?
The process typically runs three to four stages. An initial recruiter screen is followed by a hiring manager conversation focused on your operational experience and team leadership style. A technical or case round then tests your ability to diagnose pipeline issues or prioritize data quality incidents. Final rounds usually involve a panel with cross-functional partners such as engineering leads or analytics directors.
Where can I find and apply to data operations manager jobs?
You can find and apply to data operations manager jobs on Migrate Mate, which lists current openings from across the United States. Find roles that match your experience, specialization, and preferred location, then apply directly to each listing from the results on this page.
See All 395+ Data Operations Manager Jobs
Jump back to the full list of openings and apply to any data operations manager role that fits.
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