Data engineering · Data engineers

Hire Data Engineers from Canada, Latin America, and the US

Hire a data engineer to build and run the data infrastructure and pipelines your reports, applications, and AI work depend on. We find the right person, or build your entire data team, in Canada, Latin America, or the US, on a contract, permanent, or fractional basis.

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Data engineers, screened by data engineers

DevEngine is a Vancouver-based IT recruitment and staffing firm. We recruit data engineers from Canada, Latin America, and the US for contract, permanent, or fractional roles. Most of these searches are for a cloud data platform build or migration, pipelines that break too often, or analytics and AI work waiting on data no one can trust. A senior data engineer screens every candidate before you see one. You manage the day-to-day work. We handle contracts, HR, and admin.

The role

A data engineer gets reliable data where it's needed

A data engineer builds and runs the systems that collect data from across the business, clean and combine it, and deliver it to warehouses, reports, applications, and models. They decide how data moves, how often, and at what cost, and they make sure the pipelines keep working as volumes and sources change.

Typical outputs include batch and streaming pipelines, data warehouse and lakehouse models, integrations with source systems, data quality checks and monitoring, and documentation that tells others what each dataset means.

The role is often confused with two others, and organizations define all three differently. In general:

Data engineer

What they work on: The full data platform: pipelines, storage, and delivery
Core question: Is the right data arriving, clean and on time, where people need it?
Typical outputs: Pipelines, warehouse models, monitoring
Works most with: Analysts, data scientists, and platform teams
Often brought in when: A data platform needs to be built, migrated, or stabilized

ETL developer

What they work on: Extracting, transforming, and loading data between specific systems
Core question: Are these jobs moving the data correctly and on schedule?
Typical outputs: ETL jobs, mappings, load schedules
Works most with: Data engineers, DBAs, and source-system owners
Often brought in when: Integrations between systems need to be built or maintained

Data architect

What they work on: The overall design, standards, and governance of the company's data
Core question: How should our data be structured, secured, and governed?
Typical outputs: Data models, reference architectures, governance standards
Works most with: Leadership, security, and engineering teams
Often brought in when: Data has grown without a plan, or a platform decision is coming

	Data engineer	ETL developer	Data architect
What they work on	The full data platform: pipelines, storage, and delivery	Extracting, transforming, and loading data between specific systems	The overall design, standards, and governance of the company's data
Core question	Is the right data arriving, clean and on time, where people need it?	Are these jobs moving the data correctly and on schedule?	How should our data be structured, secured, and governed?
Typical outputs	Pipelines, warehouse models, monitoring	ETL jobs, mappings, load schedules	Data models, reference architectures, governance standards
Works most with	Analysts, data scientists, and platform teams	Data engineers, DBAs, and source-system owners	Leadership, security, and engineering teams
Often brought in when	A data platform needs to be built, migrated, or stabilized	Integrations between systems need to be built or maintained	Data has grown without a plan, or a platform decision is coming

If the work centers on specific integration jobs, see Hire ETL Developers. If the open question is how the data should be designed and governed, see Hire Data Architects.

When to hire

When you need a data engineer

The need usually shows up as one of these situations:

Leadership is reporting on data that broke overnight.
Pipelines fail without warning, so executive reports go out late or wrong, and analysts spend their mornings repairing data instead of producing the analysis the business needs.
A platform migration is too costly to get wrong.
Moving to a cloud data platform touches every report, model, and integration, and a team that hasn't done it before risks budget overruns, outages, and lost history.
Every new data source slows the business down.
Connecting a new system, partner, or acquisition takes weeks of custom work, so products, markets, and integrations wait on engineering capacity the team doesn't have.
AI and analytics plans are waiting on data.
The strategy is approved and the budget is set, but the data those models and dashboards need isn't clean, complete, or in one place, so nothing moves.

Need a different role?

If you need someone to build and maintain integration jobs between known systems, hire an ETL developer. If you need someone to decide how your company's data should be designed and governed, hire a data architect. We recruit for both roles.

Our screen

What our senior data engineers look for

Many candidates list the right tools but have only worked on one part of a pipeline, or never supported one in production. A senior data engineer screens every candidate and asks for specifics: the sources and volumes they handled, what broke, and how they fixed it. The answers show who has owned the work and who has only contributed to it.

Pipelines that stay up
We ask about a pipeline they built and how it held up in production. A strong data engineer can describe failures and how they made them rarer.
Data quality as part of the job
We ask how they caught bad data before it reached a report or model, and how they stopped it from coming back.
Hands-on tools and skills experience
We ask which tools they have used in production, at what scale, and for how long, then have them walk through real work in the ones your stack depends on.
Fluency with your constraints
A data engineer who has worked with your cloud, your data volumes, or regulated data reasons differently from one who hasn't. We weight that context, not only certifications.

Candidates who can list tools but not the trade-offs between them, have never owned a pipeline in production, or treat data quality as someone else's problem are screened out. Your interviews focus on fit, not filtering.

Where we source

Hire from Canada, Latin America, or the US

One search can cover all three talent pools. Brief the role once, and compare candidates from each market side by side before you decide.

Canada

Where candidates are based: Across Canada
Working hours: Canadian time zones, Pacific to Atlantic
Cost: Canadian market rates. See the Canada salary guide below.
Fits when: The role needs knowledge of the North American market, regular in-person time in Canada, or a Canadian base

Latin America

Where candidates are based: Across Latin America, including Argentina, Brazil, Colombia, Mexico, and Costa Rica
Working hours: Within 2 hours of US Eastern time, year-round. Up to 4 hours ahead of Pacific time.
Cost: Typically 35–40% below comparable North American cost. See the Latin America salary guide below.
Fits when: You want a wider candidate pool or more seniority for the budget, or the data engineer will work with a nearshore team

United States

Where candidates are based: Across the United States
Working hours: US time zones, Pacific to Eastern
Cost: US market rates.
Fits when: The role needs knowledge of the US market, regular in-person time at a US site, or a US base

	Canada	Latin America	United States
Where candidates are based	Across Canada	Across Latin America, including Argentina, Brazil, Colombia, Mexico, and Costa Rica	Across the United States
Working hours	Canadian time zones, Pacific to Atlantic	Within 2 hours of US Eastern time, year-round. Up to 4 hours ahead of Pacific time.	US time zones, Pacific to Eastern
Cost	Canadian market rates. See the Canada salary guide below.	Typically 35–40% below comparable North American cost. See the Latin America salary guide below.	US market rates.
Fits when	The role needs knowledge of the North American market, regular in-person time in Canada, or a Canadian base	You want a wider candidate pool or more seniority for the budget, or the data engineer will work with a nearshore team	The role needs knowledge of the US market, regular in-person time at a US site, or a US base

Not sure which market fits? Tell us about the role, and we'll scope it in each market and show you candidates and cost side by side.

Technology salaries in Canada and Latin America

Benchmark salaries by role and seniority before you set a budget.

Download the Canada Salary Guide Download the Latin America Salary Guide

Engagement models

Contract, permanent, or fractional

Contract

Who employs the data engineer: DevEngine
Time commitment: Full-time, for a defined period
Fits when: A platform build, a migration, or a pipeline backlog with a defined end
Placement protection: Two-week guarantee

Permanent

Who employs the data engineer: You
Time commitment: Full-time, ongoing
Fits when: Your data platform needs a standing owner
Placement protection: 180-day prorated guarantee from the start date: full refund in the first 30 days, then partial refunds on a sliding scale

Fractional

Who employs the data engineer: DevEngine
Time commitment: Part-time, hourly or monthly
Fits when: A pipeline review, a cost audit, or ongoing support for a small platform, without a full-time seat
Placement protection: Tailored to the scope of work

	Contract	Permanent	Fractional
Who employs the data engineer	DevEngine	You	DevEngine
Time commitment	Full-time, for a defined period	Full-time, ongoing	Part-time, hourly or monthly
Fits when	A platform build, a migration, or a pipeline backlog with a defined end	Your data platform needs a standing owner	A pipeline review, a cost audit, or ongoing support for a small platform, without a full-time seat
Placement protection	Two-week guarantee	180-day prorated guarantee from the start date: full refund in the first 30 days, then partial refunds on a sliding scale	Tailored to the scope of work

Each model works a little differently depending on whether you hire in Canada, Latin America, or the US. Compare the options by market to find the engagement that fits your team.

Explore services by market

How it works

How a data engineer search runs

You brief us on your current data stack, the challenges you're facing, and the scope and goals of the project.
We source for your role in Canada, Latin America, or the US, not from a bench.
A senior data engineer screens each candidate. Someone who does the same work, not a recruiter matching keywords.
You choose who to interview and who to hire.
You direct the work. On contract and fractional engagements, DevEngine holds the contract and handles payroll and compliance. On a permanent hire, the data engineer joins your payroll.
If the placement isn't working, we replace the candidate: within two weeks on contract, or under the 180-day prorated guarantee on a permanent hire.

Case studies

How this works in practice

All case studies

Technology
Scaling 14 Snowflake Consultants Across Four LATAM Markets
- 14 consultants
- ~35% lower cost
Read case study

FAQ

Data engineer hiring questions

How much does it cost to hire a data engineer?

Cost depends on four things: seniority, platform and cloud specialization, the market you hire from, and the engagement model. Hiring in Latin America typically costs 35–40% less than comparable North American hires. For salary benchmarks across technology roles, download the Canada Salary Guide or the Latin America Salary Guide. DevEngine quotes against your actual brief on the first call.

Which skills and certifications do data engineers bring?

Most work in SQL and Python, and some in Java. Typical tools include Spark, Snowflake, Databricks, and BigQuery for processing and warehousing; Apache Kafka and Apache NiFi for streaming and orchestration; AWS Glue and Azure Data Factory for cloud data integration; Informatica, Talend, and Pentaho for ETL; SQL Server, PostgreSQL, MySQL, Oracle, and Vertica databases; Kubernetes; and GitLab, GitHub Actions, or Jenkins for CI/CD. Common certifications include SnowPro Core and SnowPro Advanced: Data Engineer from Snowflake, the Databricks Certified Data Engineer Associate and Professional, the Microsoft Certified: Fabric Data Engineer Associate, the Google Cloud Professional Data Engineer, and the AWS Certified Data Engineer – Associate. Skills and certifications show familiarity, but not whether someone can keep a pipeline running. That's what the senior data engineer screen tests.

Can a data engineer lead a migration to a new data platform?

Yes, within a limited scope. A senior data engineer can plan and run a contained migration: mapping existing pipelines, moving data in stages, and validating that reports match before the old system is switched off. More complex migrations, with many source systems, a new target architecture, or governance and security requirements, need a data architect to set the design first. We can scope both roles together.

Can I hire a fractional data engineer?

Yes. A fractional data engineer works part-time, on an hourly or monthly cadence, inside your team and tools. Companies often use one for a pipeline review, a warehouse cost audit, or ongoing support for a small data platform. DevEngine places fractional data engineers from Canada, Latin America, and the US.

Should I hire a data engineer from Canada, Latin America, or the US?

Companies often choose Canada or the US when the role needs local market knowledge, regular in-person time, or a base in that country. Latin America offers a wider pool and more seniority for the budget, with working hours within 2 hours of US Eastern. DevEngine can run the search across all three markets so you can compare candidates.

Can a data engineer work with a DevEngine Engineering POD?

Yes. A data engineer can sit inside an Engineering POD or work alongside one. You choose the POD's composition and direct the work. The data engineer owns the pipelines and data models, and the rest of the POD builds on them on your sprint cadence, in your tools.

What's your interest?

Choose the path that aligns with how you want to build and scale your team.

Tell us about the scope of your data project.

We'll tell you which market and model fit, and how long the search should take.

Not ready to talk yet? Compare technology salaries in the Canada Salary Guide or the Latin America Salary Guide.