Hire senior Data Engineers who build the pipelines your AI and analytics run on — batch, streaming, and warehouse. Matched from a vetted LATAM network, in 48 hours, and yours to keep with cost-plus comp control.
Our Data Engineers work across Python and SQL with Spark, dbt, and Airflow, streaming through Kafka and Flink, and warehouses like Snowflake, BigQuery, and Databricks — on AWS, GCP, or Azure. A representative sample, not a checklist.
Python
Languages
SQL
Languages
Scala
Languages
Java
Languages
Spark
Data & Analytics
Databricks
Data & Analytics
Snowflake
Data & Analytics
dbt
Data & Analytics
Airflow
Data & Analytics
Dagster
Data & Analytics
Kafka
Data & Analytics
Flink
Data & Analytics
Fivetran
Data & Analytics
Airbyte
Data & Analytics
BigQuery
Data & Analytics
Redshift
Data & Analytics
Kinesis
Data & Analytics
Hadoop
Data & Analytics
Hive
Data & Analytics
Trino
Data & Analytics
Delta Lake
Data & Analytics
AWS
Cloud & DevOps
GCP
Cloud & DevOps
Azure
Cloud & DevOps
Terraform
Cloud & DevOps
Docker
Cloud & DevOps
Kubernetes
Cloud & DevOps
AI-fluent by default
Every candidate is screened for how they actually work with AI — not just whether they’ve used it. We match you to the exact AI-driven workflows your team relies on.
How to hire your Data Engineer
1
Open your position
Post your role risk-free. You won’t pay until you make a hire.
2
Review candidates in 48 hours
We match you with senior, vetted candidates who’ve actively expressed interest in your role — interviews, not résumés.
3
Hire — and keep them
We handle compliance, payments, and equipment. You control comp with our cost-plus model, so your best people stay.
Data Engineers build the pipelines and infrastructure your analytics and AI run on — moving data from source to warehouse, clean and reliable, at any scale. They design for throughput and trust: batch and streaming pipelines, well-modeled warehouses, and data quality you can build on. That work increasingly extends to AI — the retrieval and feature infrastructure, vector databases and feature stores, that power models and LLM applications.
Core responsibilities
Build batch and streaming data pipelines
Design and model data warehouses for analytics and ML
Ensure data quality, reliability, and lineage
Build vector and feature infrastructure for AI workloads
Partner with data science and analytics to ship end to end
Not your traditional staff aug.
Remotely's Transparent Staff Aug
You choose the candidates, and they choose you too
You control compensation and retain the best talent
7,000+ developers analyzed for proven experience
AI-fluent and startup-minded
Speed and visibility powered by a tech-enabled platform
Engineers who stay for the long haul.
Traditional Staff Aug
Developers are assigned, not aligned
The agency controls the paycheck
Limited pool, limited options
Code monkeys with no business sense
Powered by emails & spreadsheets
Here today, gone tomorrow
Data Engineers in your time zone
Our talent works across Latin America — Brazil, Mexico, Colombia, Argentina, Chile, and beyond — on US business hours. Most of the region sits within a few hours of US Eastern time, so you get a full workday of overlap: standups, pairing, and code review happen in real time, not overnight.
And they communicate like teammates, not vendors — fluent, professional English and a startup-ready working style.
Where they work
Brazil
Mexico
Colombia
Argentina
Chile
+ 12 more
Frequently asked questions
How does Remotely screen for AI fluency?
What does it cost to hire with Remotely?
What is Remotely's vetting process for Data Engineers?
How is Remotely different from other remote job marketplaces?
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