What Is an Analytics Engineer? | LatamCent Hiring Glossary
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What Is An Analytics Engineer?

An analytics engineer turns raw warehouse data into clean, tested, documented models that analysts and BI tools can trust. The role sits between data engineering and data analysis, writing SQL-based transformations, usually in dbt, so the rest of the company doesn’t have to re-derive the same business logic every time they build a report.

Also called
BI Engineer, Data Analytics Engineer
Reports to
Head of Data / Director of Analytics
Works on
dbt models, SQL transformations, data warehouse
Measured on
Data model reliability (test coverage)

What An Analytics Engineer Actually Does

  1. 01 · ModelingWrites SQL-based transformations, usually in dbt, to turn raw warehouse data into clean, tested, documented models
  2. 02 · Warehouse DesignDesigns the data warehouse’s schema and data marts so analysts and BI tools can self-serve without re-deriving logic
  3. 03 · Testing & DocsOwns data testing and documentation, catching broken metrics before they hit a dashboard
  4. 04 · PartnershipPartners with data engineers on pipeline architecture and with analysts and stakeholders on what metrics actually mean
  5. 05 · Metric OwnershipMaintains the source-of-truth definitions for core business metrics, like what counts as an active user

Analytics Engineer Vs. Similar Roles

RoleMain focusPrimary metric
Analytics EngineerTransforms raw data into clean, modeled dataData model reliability, test coverage
Data EngineerBuilds and maintains pipelines and infrastructurePipeline uptime, data freshness
Data AnalystInterprets data to answer business questionsReport accuracy, insight impact
Data ScientistBuilds predictive models and statistical analysisModel accuracy, business impact

At smaller companies, one person often covers both analytics engineering and data engineering, or both analytics engineering and analyst work. Split the roles once the data team is big enough that pipeline work and modeling work are competing for the same person’s time.

Skills To Screen For

Strong SQL and hands-on dbt experience (models, tests, docs, sources) Comfortable working directly in a cloud warehouse (Snowflake, BigQuery, Redshift) Understands dimensional modeling and star-schema basics Business-level English to translate stakeholder questions into data models

Interview Questions Worth Asking

1"Walk me through how you’d model a raw events table into something analysts can actually use."
2"Tell me about a broken dashboard you traced back to a data problem. How did you find it?"
3"How do you decide what belongs in a shared dbt model versus a one-off query?"

Hiring An Analytics Engineer In Latin America

How Much Of The Workday You’d Share

Your team’s time zone
Clock
Your team, 9am to 5pm Their workday, 9am to 6pm local Shared hours
Colombia
Mexico
Brazil
Argentina

Bogota, Mexico City, Sao Paulo, and Buenos Aires don’t change their clocks, so the overlap shifts when yours does. Times shown are in your team’s time zone. National English-proficiency averages vary by market too: Argentina ranks in EF’s "High" band globally, while Colombia, Mexico, and Brazil sit in the "Low" band. Screen every candidate’s spoken English directly rather than assuming by country.

Common mistake: hiring a data analyst or generalist BI person into an analytics-engineering seat and expecting them to own transformation logic and testing discipline. The role needs someone comfortable being judged like a software engineer, with version control, testing, and code review, not just someone good at writing queries.

What It Costs

US average $109K/yr $82K-$123K salary range
LatAm average (4+ yrs) $58K-$67K/yr Senior, remote-for-US pay
Typical savings ~43% About $42K-$51K/yr per hire
CountryEntry level (1-3 yrs)Senior (6+ yrs)
Colombia$25K/yr$63K/yr
Mexico$29K/yr$58K/yr
Brazil$35K/yr$67K/yr
Argentina$29K/yr$67K/yr
21 days

Typical time from kickoff to signed offer. LatamCent delivers 3 to 5 candidate profiles in the first 10 days.

Frequently Asked Questions

A data engineer builds and maintains the pipelines and infrastructure that get raw data into the warehouse, and is measured on pipeline uptime and data freshness. An analytics engineer takes it from there, modeling that raw data into clean, tested datasets analysts and BI tools can trust, and is measured on data model reliability and test coverage.

A data analyst interprets data to answer business questions and is measured on report accuracy and insight impact. An analytics engineer builds and tests the underlying models the analyst queries, usually in dbt, and is held to the same standards as a software engineer: version control, testing, and code review.

US analytics engineers average around $109K a year, with a typical range of $82K to $123K. Analytics engineers with 4 or more years of experience in Latin America typically run $58K to $67K a year for the same seniority, roughly 43% less.

Most searches run 21 days from kickoff to a signed offer, with 3 to 5 candidate profiles delivered in the first 10 days.

Yes. Colombia, Mexico, Brazil, and Argentina all sit within a few hours of US time zones, so most teams get 6 to 8 shared working hours a day depending on which US time zone they’re in, plenty for standups and pairing on data models.

Need An Analytics Engineer On Your Team?

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