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Loka · Remote · North Macedonia +2 more
Cloudbeds · Remote · South America or North America
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Columbia University · Hybrid · New York, NY, USA
Columbia University · Hybrid · New York, NY, USA
Columbia University · Hybrid · New York, NY, USA
University of Chicago · Onsite · Chicago, IL, USA
Policy Expert · Hybrid · London, UK
George Washington University · Hybrid · Washington, USA
Cornell University · Onsite · Ithaca, NY, USA
Northwestern University · Onsite · Chicago, IL, USA
Samsara · Hybrid · Mexico City, Mexico
Northwestern University · Onsite · Chicago, IL, USA
Northwestern University · Onsite · Evanston, IL, USA
S&P Global · Hybrid · Toronto, ON, Canada
Columbia University · Hybrid · New York, NY, USA
Columbia University · Hybrid · New York, NY, USA
Northwestern University · Onsite · Chicago, IL, USA
Showing 19 of 22
Employers hiring for Data Cleaning on this page include Columbia University, Northwestern University, and Loka. Data Cleaning roles appear most frequently in engineering, data, and platform teams at companies that offer a 4-day week or another flexible schedule. Each listing indicates the seniority level and whether Data Cleaning is a primary requirement or one of several preferred skills — expand any role above to see the full stack and responsibilities.
Data Cleaning roles on this page span seniority levels, from entry-level and mid-level through senior, lead, and staff or principal positions. Filter by level in the sidebar to narrow the list above to the ones that fit you.
Lead with measurable outcomes over time spent — Data Cleaning hiring managers at companies that run 4-day weeks or flexible schedules care about delivered value, not hours worked. Highlight projects where you shipped at a steady cadence, collaborated asynchronously, or reduced engineering toil through automation or tooling. Include concrete metrics (latency improvements, adoption numbers, cost reductions) rather than vague duty descriptions. Expand listings above to see the exact framing each employer uses in their job descriptions.
Pay depends on the role, seniority, location, and employer — not on the schedule alone. Data Cleaning roles in tech and data typically command premium rates, and specific ranges depend on seniority and sub-specialty (e.g. backend vs frontend, infra vs ML). Individual listings above show exact bands where the employer publishes them.
Depends on the role, but Data Cleaning candidates who also demonstrate async communication, clean documentation, and cross-functional collaboration are typically strong fits for employers that run 4-day weeks or flexible schedules — those teams rely on written-first communication and high-context handoffs. Technical-adjacent skills vary by stack. Browse the top skills shown in the sidebar to see which tags co-occur most often with Data Cleaning on current listings.
Work-life balance
85+ excellent, 70+ great, 55+ good. How we score
Schedule
Work-life balance
85+ excellent, 70+ great, 55+ good. How we score
Schedule
