A data engineer builds and maintains the data infrastructure that powers analytics and data science - designing pipelines, data warehouses, and the architecture that makes data accessible and reliable.
A great Data Engineer does not just complete tasks. They own a function that directly frees you to grow. Here is what that looks like in a scaling business:
01Build and maintain data pipelines from source systems to the data warehouse
02Design and implement the data warehouse schema and data models
03Ensure data quality, reliability, and freshness across the data platform
04Collaborate with analysts and scientists on data access and tooling
05Manage and optimize the data infrastructure for performance and cost
How this hire moves your business forward: Data engineering is the foundation that makes all your analytics possible. Without reliable data infrastructure, your analytics team spends most of their time cleaning data instead of generating insights.
Why LatAm
Why LatAm Produces Great Data Engineers.
LatAm data engineers are strong in modern data stack tooling including dbt, Airflow, Spark, and cloud data warehouses. Many have built data platforms for US-facing companies and understand the full modern data stack.
The timezone overlap with the US is strong. LatAm professionals work within 1 to 3 hours of US Eastern time, so there is no async lag, no late-night handoffs, and no communication gap.
Skills & tools
Know What a Great Data Engineer Actually Brings to the Table.
Beyond the resume, here are the skills, tools, and traits that separate strong performers from strong interviewers.
Hard Skills
Data pipeline development (Airflow / Prefect)
Data warehouse design (Snowflake / BigQuery / Redshift)
dbt for data transformation
SQL and Python
Data quality management
Common Tools
Airflow / Prefect
dbt
Snowflake / BigQuery / Redshift
Python
Spark
Soft Skills & Traits
Reliability-obsessed about data
Collaborative with analytics consumers
Strong documentation discipline
Proactive about data quality
Cost-conscious about infrastructure
Compensation
What You Can Expect to Pay.
Based on Sur market data and regional benchmarks. Figures reflect total cash compensation.
Seniority
US Annual
LatAm Annual
You Save
Entry
$80,000
$30,000
$50,000 / yr
Mid level
$110,000
$42,000
$68,000 / yr
Senior
$145,000
$57,600
$87,400 / yr
Spot the right hire
What to Look For, and What to Watch Out For.
Green Flags
Has built production data pipelines that analysts depend on daily
Data models are documented and understandable to the analytics team
Data quality monitoring catches issues before analysts encounter bad data
Infrastructure costs are managed and optimized proactively
Red Flags
Can build pipelines but has never worked at production scale
No data quality monitoring or alerting in place
Data models only they can understand
Our process
Our Process for This Role.
We do not post and wait. Every Data Engineer search we run is built from scratch around your business, your stage, your team, and your goals. And at every step, we are thinking about how this hire helps you grow.
1
Onboarding Call
We start by understanding what you actually need.
2
Role Scoping and Assessment Design
We build a precise role profile and design the custom skills assessment before we search for anyone.
3
Sourcing
We source actively across LatAm and the Caribbean and through our network.
4
Prescreening and Phone Screen
Every candidate is internally screened then put through an English phone screen.
5
Your Shortlist
3 to 5 candidates delivered early in the process with background, audio clip, and our team's recommendation.
6
Skills Assessment
Shortlisted candidates take a custom assessment built to replicate the actual work of the role.
7
Hire and Guarantee
We support the offer, help structure compensation for retention, and back every placement with a 90-day guarantee.
3-4 weeks typically. Most placements are made within 21 days of the onboarding call.
Most LatAm professionals work within 1 to 3 hours of US Eastern time.
All Sur placements speak fluent English. We screen for language ability on every search. Moderate English acceptable depending on exposure.
A LatAm data engineer delivers the same data infrastructure capability as a US hire at 35-45% of the cost. Modern data stack expertise (dbt, Airflow, Snowflake) is widely available and growing rapidly in LatAm.
If your hire does not work out within the first 90 days for any reason, we replace them at no additional cost.
dbt for transformation, Airflow or Prefect for orchestration, and Snowflake, BigQuery, or Redshift for the warehouse are the most common combinations.
A data analyst answers business questions with data. A data engineer builds the infrastructure that makes data available to analyze. You typically need both.
Ready to Hire a Data Engineer Who Actually Moves the Needle?
Let us design the role together and find you the right person from LatAm.