ALL ROLES / DATA ENGINEERS
Hire a data engineer who keeps your pipelines running
An alternative to a data engineering services firm. One dedicated data engineer from Latin America who builds and owns your pipelines, your warehouse and your data models, and works your hours with your team.
TRUSTED BY TEAMS WHOSE CLOUDTASK HIRES HAVE STAYED 5 TO 8 YEARS
How it works
How do I hire a data engineer?
You do one thing: interview. We handle everything else.
Post the role
5 minutes. The role, the motion, the tools, the comp band. That is all we need to start.
Review your matches
3 to 5 matches in 48 hours.
Interview and hire
We coordinate interviews. On Managed Staffing, we also handle payroll and compliance across LATAM.
WHY TEAMS TRUST CLOUDTASK
What you get with every hire
One engineer, your data
A dedicated person who learns your sources, your schemas and your business logic. Not a services team that rotates people between clients.
Same hours as your team
Latin America and the Caribbean overlap the US working day, so a failed load or a broken dashboard gets fixed before the morning meeting, not the next day.
Checked on your stack
SQL, Python, your warehouse, your orchestrator and your cloud. We screen each candidate against the tools you name in the brief.
Replacement guarantee
24 months on Managed Staffing, 6 months on Direct Hire. Data work builds on itself, so the guarantee covers the case where the fit turns out to be wrong.
WHY CLOUDTASK
Staffing with numbers behind it
10,000+
hires placed
since 2016
85%
still in seat
past 90 days
24 months
replacement guarantee
on Managed Staffing
12
countries
across Latin America and the Caribbean
PRICING MODEL
Managed Staffing.
Managed Staffing is open to every role we place. We find the person, handle payments and compliance, and stay involved after the hire with check-ins, visibility, and escalation when something is off. You get the person. We keep the machine running. For roles that create demand, outbound SDRs, BDRs, demand generation and full-cycle AEs, Managed Staffing runs on a six-month minimum term.
Pay
One all-in monthly rate
Per person. That is the number, and there is nothing added to it.
In the monthly rate
- Sourcing from the CloudTask staffing and recruiting company
- Screening and vetting
- Matching coordination
- Worker payments
- Compliance and employment administration
- Onboarding support at day 0, 7, 30 and 60
- Ongoing check-ins with the hire and with you
- Time and activity tracking, on by default
- Performance escalation
- 24-month replacement guarantee. Replacements not capped.
- Health benefits available on request
- Equipment benefits available on request
Stays with you
- The work itself
- Priorities and direction
- Who you hire
$299 to start your search. One time, not a subscription. It applies to your buyout or toward your first placement.
Start your searchPRICING MODEL
Direct Hire.
Direct Hire is open to every role we place. We find the person, vet them, and hand them over. You employ them, you manage them, you own the relationship from day one. Roles that create demand usually land here, because live call feedback and daily coaching work best coming straight from your sales leader, and there is no minimum term.
Pay
20% to 30%
Of first-year base salary. One time, quoted per role, paid when they accept.
In the fee
- Sourcing from the CloudTask staffing and recruiting company
- Screening and vetting
- Shortlist of matched candidates
- Interview coordination
- Offer support
- 6-month replacement guarantee. One replacement, same job description.
Yours when they accept
- Employment and payroll
- Compliance and employment administration
- Ongoing management
- Time and activity tracking
- Health benefits and equipment benefits
$299 to start your search. One time, not a subscription. It applies to your buyout or toward your first placement.
Start your searchHow CloudTask compares
Run the numbers. We did.
The same role, three ways to fill it.
Swipe to compare
| US Direct Hire | Staffing Agency | ||
|---|---|---|---|
| Time to First Interview | 48 hours | 3 to 6 weeks | 2 to 4 weeks |
| Payroll & Compliance | Included on Managed Staffing | You manage | Included in rate |
| Vetting Process | Human + AI verified | You screen | Recruiter screened |
| Candidate spam | Screened out before you see a profile | Common | Low |
| Tool Verification | Verified per candidate | Self-reported | Rarely verified |
| Free Replacements | 24 months on Managed Staffing, 6 months on Direct Hire | None | Variable |
Testimonials
Trusted by teams that hire with us
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LATAM has been a gold mine for talent. Our CloudTask hires understand our company culture and mission, and they connect with our customers in a way that drives high NPS and CX scores.
David Barrett CEO, Expensify -
At first we were an SF-based team only. Then I met Amir Reiter back in 2018. After visiting Medellín, I knew LATAM would be key to our growth and success.
Tim Zheng CEO, Apollo.io -
After meeting my CX and CS team in Medellín, we immediately loved the culture and the work ethic. As a European-HQ company, we found LATAM to be perfect to service our American clients.
Carl Carell CRO and Co-founder, GetAccept
SKILLS
Top capabilities to look for in a data engineer
A good data engineer is measured by data that arrives on time, matches the source and can be trusted by the people who use it.
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SQL and Python, fluently
Complex joins, window functions and query tuning in SQL, and clean, tested Python for the transformations SQL cannot handle well.
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Pipelines and orchestration
Building batch and incremental pipelines and scheduling them with an orchestrator such as Airflow, Dagster or Prefect, with retries and alerts.
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Cloud warehouses
Snowflake, BigQuery, Redshift or Databricks: loading, partitioning, cost control and access management on the platform you run.
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Data modeling
Dimensional models and clear table design, often with dbt, so analysts query one trusted version of each metric.
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Data quality and testing
Tests on freshness, volume, nulls and duplicates, and monitoring that flags a problem before a stakeholder finds it in a report.
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Source integrations
Pulling from APIs, product databases, CRMs and SaaS tools, with managed connectors where they fit and custom code where they do not.
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Security and governance
Role based access, handling of personal data, documentation of lineage, and keeping credentials out of code.
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Working with analysts
Turning vague questions from analytics, finance or product into tables that answer them, and saying early when a request needs a new source.
HIRING GUIDE
How to hire a data engineer
Most companies searching for data engineering services need someone to build pipelines and keep them healthy. This guide covers what a data engineer does, when a services firm is the better choice, and what to check before you hire one for your team.
What exactly does a data engineer do?
A data engineer moves data from where it is created to where it is used. That means extracting it from applications, databases and SaaS tools, cleaning and modeling it, and loading it into a warehouse where analysts, dashboards and models can rely on it.
The job does not end at the first pipeline. Most of the value is in keeping pipelines running as sources change: fixing failed loads, handling schema changes, controlling warehouse cost and adding new sources as the business asks new questions.
Data engineering services firm or a dedicated engineer?
A services firm is the right choice for a defined project with a start and an end: a warehouse migration, a first platform build, or an architecture review. You get a team and a delivery plan, and the engagement closes when it ships.
A dedicated data engineer is the right choice when the work is continuous. New sources, new questions and broken loads arrive every week, and a person who already knows your data answers them faster than a firm you brief again each time.
When should you not hire a dedicated data engineer?
When your data fits in a few spreadsheets and one BI tool with built-in connectors. A managed connector plus a part-time analyst will often cover it, and a full-time engineer will not have enough to do.
It is also the wrong first hire when nobody has decided what questions the data should answer. Start with an analyst or a clear list of reports; a data engineer builds much better when the use cases are known.
Data engineer, data analyst or data scientist?
The data engineer builds and maintains the pipelines and the warehouse. The data analyst uses that data to answer business questions and build reports. The data scientist builds statistical and machine learning models on top of it.
Many small teams hire an analyst first and a data engineer second, once the analyst spends more time fixing data than analyzing it. That moment is usually the clearest signal that the role is needed.
What should I check in the interview?
Give a small, real task: a raw export from one of your sources and a question to answer. Look at how the candidate cleans the data, how they model it, and whether they test the result against the source.
Then ask how they would handle a pipeline that fails at night, and how they would know it failed. A good answer covers retries, alerts, idempotent loads and who gets notified, not only the code.
Red flags in data engineer candidates
Output never checked against the source. In the task with your raw export, notice whether they compare their result with the source before calling it done. A candidate who does not will ship tables that look right and are not.
Failures found by stakeholders. Ask how they would know a pipeline failed at night. If the answer is that someone would notice the dashboard, there are no alerts or quality tests, and your team will find the problems first.
Loads that cannot run twice. When you ask about a failed load, listen for retries and idempotent loads. A candidate who reruns jobs by hand and removes duplicates afterwards will leave that cleanup to your team.
Pipelines without a model. A candidate who talks about moving data but not about how the tables are designed for the people who query them builds warehouses where every analyst calculates the same metric a different way.
No questions back. Ask how they handled a vague request from analytics, finance or product. Someone who built exactly what was asked, without clarifying the question or saying early that it needed a new source, will build tables that answer the wrong thing.
Is AI replacing data engineers?
AI tools already write first drafts of SQL, transformations and documentation, and a good data engineer uses them. What they do not replace is knowing your sources, your business definitions and why a number changed.
If anything, teams building AI features need more clean, well modeled data, not less. The role shifts toward quality, governance and feeding reliable data to models.
How much does it cost to hire a data engineer?
It depends on seniority, the stack, the language requirement and the country the person works from, and any single number describes one scenario and calls it a price.
What is worth understanding is the shape. On Managed Staffing it is one all-in monthly rate per person with payments, compliance and replacement cover inside it. On Direct Hire it is a one-time fee and the person goes on your payroll. We quote your number before you interview anyone.
Why hire a data engineer in Latin America?
Overlap. Pipelines fail at inconvenient times and stakeholders notice in the morning. An engineer who works the same hours as your team can fix it before the first meeting and talk it through with the person who found it.
The second reason is communication. Data engineering is full of definitions that need to be agreed in plain language, and your engineer works with your team in English every day. We screen that live on a call.
How does CloudTask hire for this role?
You send the stack, the kind of work and the hours you need covered. We source against that brief and come back with 3 to 5 matched profiles within 48 hours, each one screened on a live call and checked against the tools you named.
You interview and choose. On Managed Staffing we handle payments, compliance and onboarding and stay involved with check-ins. On Direct Hire the person joins your payroll from day one. Both carry a replacement guarantee: 24 months on Managed Staffing, 6 months on Direct Hire.
FAQ
The fine print, in plain terms.
How much does it cost to hire a data engineer instead of a services firm?
Should I use a data engineering consulting firm instead?
Can a data engineer work on our existing stack?
What is the $299 for?
Why is there no number on the monthly rate?
Who is the legal employer?
How does tracking work, and can I turn it off?
What happens if the person does not work out?
Is there a platform or subscription fee?
Ready to hire?
3 to 5 matches in 48 hours. Start with a quick role brief to get your shortlist.