A senior data engineer has a median client bill rate of $54 an hour in Mexico, $64 in Brazil and $52 in Colombia, per Plugg's 2027 hiring report, which groups AI and data engineers together. Plugg sends a vetted shortlist in about 3 days, and your engineer works US hours.
What a data engineer costs per hour in Latin America
| Role | Mexico | Brazil | Colombia |
|---|---|---|---|
| AI / Data engineer | $54 (18) | $64 (11) | $52 (8) |
How to read these rates
What the figures are. Median client bill rates in US dollars per hour, by role and country, from Plugg Technologies' own engagement data as published in the 2027 Latin America Tech Hiring Report. The number in parentheses is how many engagements sit behind each median.
Bill rate is not pay. The bill rate is what the client pays. The contractor's pay is lower. For senior and lead engineers the report shows contractor pay of $30 to $38 an hour against a client bill rate of $44 to $52.
Do not stack these with the country-level medians. The report also cites country-level software engineer medians. It says they are reported separately and do not reconcile with this table, so each page here uses one or the other.
These are illustrative medians from a Plugg sample, not a quote. Your rate depends on the role, seniority, stack and country. Request talent rates for a real number.
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Request Talent RatesDashboards, reports and AI features are only as good as the data under them, and data engineers keep that layer trustworthy. The 2027 hiring report notes that Plugg recruiters see growing demand for data roles as a stepping stone to AI functionality. This page covers what data engineers cost in Latin America and what to screen for.
What a data engineer does
A data engineer moves data from where it is created to where it can be used. That means pulling it from product databases, SaaS tools and event streams, cleaning and modeling it, loading it into a warehouse and keeping the pipelines on schedule. On a US team they work with analysts and scientists who query the data, and with backend engineers who produce it.
The work is quiet and the failures are loud: a broken pipeline means a wrong number in front of the executive team. Look for people who care about tests, lineage and alerting on their own pipelines.
Skills and stack to look for
- Languages: SQL at a high level, plus Python, and Scala or Java where Spark is in use
- Warehouses and lakes: Snowflake, BigQuery, Redshift or Databricks, and an opinion on partitioning and cost
- Transformation: dbt, with tests, documentation and a sensible model layout
- Orchestration: Airflow, Dagster or Prefect, with retries, backfills and alerts
- Streaming and scale: Kafka or Kinesis, and Spark for large batch jobs
- Cloud basics: AWS, GCP or Azure, IAM and cost control
What affects the rate
The report reports AI and data engineers as one row, with medians between $52 and $64 an hour by country. Seniority and stack depth move the number more than anything else. An engineer who has designed a warehouse from scratch costs more than one who maintains existing models, and streaming experience adds a premium. Sample sizes are modest, from 8 engagements in Colombia to 18 in Mexico.
How Plugg screens, and what to test yourself
Plugg screens candidates against your hiring bar and for advanced-level English communication before you see a profile. You then interview the shortlist and decide.
For a data role, test SQL and judgment together. Give the candidate a messy sample dataset and ask how they would model it, then have them write a query that answers a business question and explain what could make the answer wrong. Ask how they would find out that yesterday's load failed and how they would backfill it.
When to hire a data engineer
- Analysts spend their week cleaning exports and rebuilding the same spreadsheet
- Reports disagree because every team defines a metric differently
- You are moving from a single reporting database to a warehouse
- You want to ship AI features and the underlying data is not ready
Where to hire data engineers
Colombia and Mexico sit on or near US Central time, which helps when a pipeline fails and someone has to respond. Brazil and Argentina have deep engineering communities and overlap with a US Eastern afternoon. For the models that sit on top of the data, see AI engineers.