
Data Engineer
Remote · USContract / Temporary$53/hrSeen todaySeen in employer's feed today
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At a glance
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Requirements
Credentials this posting asks for.
Job overview
The Data Engineer builds data models and allocation logic for cloud-cost showback and chargeback. The role covers allocation rules, amortization, shared-cost distribution, untagged-cost attribution, budget variance, and forecasting models. It requires SQL, data engineering, cost allocation, dimensional modeling, and familiarity with FinOps methodologies and financial accounting concepts. Prior experience building chargeback or showback systems is described as ideal.
Skills & qualifications
Skills
Qualifications
Full job description
Job Title: Data Engineer
Location: Remote
Duration: 6 Months
Pay rate: $ 53/hr on W2
Job Description:
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Does the resource have to be Local: No
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Does this role have any *Visa Restrictions? None
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What type of education is needed for this position? Bachelors Degree of any IT related courses
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Work location : US Remote
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Will this role work remote/In Office/Hybrid: Remote
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Does this role require vaccination mandate? NA
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Will the client pay for travel and expenses? No
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Is industry experience needed for this role and why? 5+ years
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What are must-have skills for this role?
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SQL
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Data Engineering
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Cost Allocation
- Years of experience required for each skill? 5
Responsibilities :
This engineer builds the data models that allocate, attribute, and distribute cloud costs to business dimensions, enabling showback and chargeback capabilities.
5-7 years of data engineering experience
This is the most complex position from a business logic perspective. Building allocation rules, amortization calculations, and understanding how to model financial constructs requires both technical depth and domain experience. Ideally someone who has built chargeback/showback systems before.
Engineering Responsibilities:
Design allocation rule engine supporting tag-based, account-based, and custom mappings
Build amortization models for upfront payments (1-year, 3-year commitments)
Implement shared cost distribution models (proportional, even split, fixed coefficient)
Create untagged cost attribution logic using account ownership and heuristics
Build budget vs. actual variance models
Design forecasting input models based on historical trends
Ensure data models align with accounting periods and matching principles
Technical Skills required:
Expert SQL and dimensional modeling
Experience building allocation and chargeback systems
Understanding of FinOps cost allocation methodologies
Data modeling tools (dbt, LookML, or similar)
Understanding of financial accounting concepts (amortization, accruals)
ManpowerGroup is committed to providing equal employment opportunities in a professional, high quality work environment. It is the policy of ManpowerGroup and all of its subsidiaries to recruit, train, promote, transfer, pay and take all employment actions without regard to an employee's race, color, national origin, ancestry, sex, sexual orientation, gender identity, genetic information, religion, age, disability, protected veteran status, or any other basis protected by applicable law.
How this job compares
Set against the 6,271 open Data Engineer jobs on Olive Jobs, counted November 7, 2026.
- Pay
- This posting$53/hr
- California median$70–81/hr38 hourly ranges
- US median$65–76/hr255 hourly ranges
This rate, $53/hr, is 30% below the California median midpoint ($76/hr) — in the lowest quarter of Data Engineer hourly ranges in California.
- Openings
- Olive Jobs lists 897 open Data Engineer jobs in California and 6,271 across the US. 8% of them nationwide are listed as remote or flexible.
- Experience
- This posting asks for at least 5 years of experience; Data Engineer postings that state a minimum ask for 5 years at the median (5,462 postings).
- Education
- This posting asks for a bachelor's degree; 2,408 of the 6,271 open Data Engineer jobs (38%) ask for a bachelor's degree or higher.
Counted across the open, public US postings on Olive Jobs on November 7, 2026. Pay medians are the middle values of the low ends and of the high ends of postings that list both ends of a range in the same cadence (a yearly salary or an hourly rate); a range's midpoint is halfway between its ends. Pay and experience figures resting on fewer than 20 postings are left out.
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