Data Operations Associate
- Market p25–p75
- $100k–$150k
- Opened · 30d
- +0
- Closed · 30d
- −0
- Opened · 7d
- +1226% of open
- All software engineering
- 75,162open
About Qualitate
Qualitate is building the AI-native continuous intelligence platform for enterprises, investment firms, and asset managers. We automate the entire primary research workflow, from study design and expert recruitment through AI-moderated interviews and insight synthesis, replacing weeks of manual research with high output signal in hours.
Primary research remains slow and transactional for everyone involved. Investment and corporate strategy teams spend hundreds of hours coordinating intermediaries, scheduling calls, and synthesizing fragmented insights. Experts face repetitive outreach, screener calls, schedule wrangling, and one-off engagements that offer them little control or lasting value.
Qualitate transforms this experience with an AI-native expert network platform that gives participants the flexibility to contribute on their own time while enabling research at unprecedented scale. Qualitate’s AI Moderator conducts thousands of conversations with experts each month, capturing forward-looking purchasing plans, competitive displacement, and real-time ROI signals. Our continuous intelligence platform then turns these conversations into quantified, time-series outputs tracking over 10,000 public and private companies, queryable instantly in natural language. Our customers include some of the world's largest enterprises, hedge funds, PE firms, credit investors, and venture capital firms.
The Role
Data is the foundation of everything we build, and as a Data Operations Associate at Qualitate, you'll be part of the core team that keeps that foundation solid. Reporting to the Director of Data Strategy & Operations, you'll sit at the intersection of data quality, process, and tooling – making sure the information flowing through our systems is accurate, reliable, and ready to be trusted by our clients and internal teams. This is a hands-on, high-ownership role. You'll build and refine the pipelines and QA processes that catch problems before they spread, untangle the tricky edge cases, and design the workflows that let us scale without sacrificing quality. You'll have real room to bring your own ideas and grow your technical skills as the team evolves. If you like turning chaos into clean, dependable systems and want to shape how a fast-growing team operates, this is the role for you.
What You’ll Own
Manage data QA processes. Iterate on existing workflows to improve them and create new processes from scratch.
Handle data escalations. Resolve data errors quickly as they arise, digging into root causes and fulfilling ad-hoc data requests.
Build compliance guardrails. Bake them into data processes so sensitive information is handled correctly by default.
Drive end-to-end survey launches, partnering with our Intelligence Strategy & Ops and Market Research teams to deliver on quarterly goals.
Tackle unstructured data. Develop new approaches for handling it, and build out AI skills and tooling to make the team's work more efficient.
Manage offshore service provider relationships, developing reporting and tracking tools that improve productivity and keep work aligned with service-level agreements.
Maintain SOPs. Document and maintain standardized operating procedures, so processes stay consistent and repeatable across the org as we scale.
Who This Role Is For
You have 2+ years in Data Operations or as a QA analyst, with a track record troubleshooting data errors, escalations, and edge cases.
Data quality is top of mind. You have a strong track record of implementing data validation, cleaning, and quality-assurance processes.
You're proficient in SQL and Excel/Google Sheets, and you use AI tools to speed up your work.
You’re detail oriented. Small errors don't slip past you, and you communicate clearly about what you find and how you're resolving it.
You want real ownership. This is a lean team, so you'll have direct accountability for the systems you build and room to shape how we operate.
You're comfortable with ambiguity. Early-stage data infrastructure is messy—you're energized by building order out of that, not frustrated by it.