Data engineering · Data analysts

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

Hire a data analyst to turn large datasets into the reports, dashboards, and insights on performance, customers, and market trends that improve operations and customer experience. 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 analysts, screened by data analysts

DevEngine is a Vancouver-based IT recruitment and staffing firm. We recruit data analysts from Canada, Latin America, and the US for contract, permanent, or fractional roles. Most of these searches are for teams that have data but not answers: reports no one trusts, dashboards no one opens, or questions from leadership that take weeks to answer. A senior data analyst screens every candidate before you see one. You manage the day-to-day work. We handle contracts, HR, and admin.

The role

A data analyst helps the business make better decisions

A data analyst collects, processes, and analyzes the data a company already has to answer business questions. They pull and clean data from operational systems, define the metrics that matter, spot trends in performance, customer preferences, and the market, and build the reports and visualizations people use to run the business. Their work helps leadership improve operations and the customer experience.

Typical outputs include recurring KPI reports and dashboards, ad hoc analyses for leadership, metric definitions everyone agrees on, data quality checks, and written findings that recommend what to do next.

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

Data analyst

What they work on: Analysis of business performance: what happened, why, and what it means for operations and planning
Core question: What do the numbers say, and what should we do about it?
Typical outputs: Dashboards, KPI reports, analyses, metric definitions
Works most with: Business leaders, operations, finance, and marketing
Often brought in when: Leaders need reliable answers from data they already have

Data scientist

What they work on: Predictions and models about what is likely to happen
Core question: What can we predict or automate with this data?
Typical outputs: Statistical models, forecasts, machine learning prototypes
Works most with: Product, engineering, and data teams
Often brought in when: A business problem calls for prediction, not reporting

Data engineer

What they work on: The pipelines and platforms that move and store data
Core question: Is the right data arriving, clean and on time, where people need it?
Typical outputs: Data pipelines, warehouses, data models, integrations
Works most with: Data analysts, data scientists, and platform teams
Often brought in when: Data is scattered, late, or unreliable at the source

	Data analyst	Data scientist	Data engineer
What they work on	Analysis of business performance: what happened, why, and what it means for operations and planning	Predictions and models about what is likely to happen	The pipelines and platforms that move and store data
Core question	What do the numbers say, and what should we do about it?	What can we predict or automate with this data?	Is the right data arriving, clean and on time, where people need it?
Typical outputs	Dashboards, KPI reports, analyses, metric definitions	Statistical models, forecasts, machine learning prototypes	Data pipelines, warehouses, data models, integrations
Works most with	Business leaders, operations, finance, and marketing	Product, engineering, and data teams	Data analysts, data scientists, and platform teams
Often brought in when	Leaders need reliable answers from data they already have	A business problem calls for prediction, not reporting	Data is scattered, late, or unreliable at the source

If the need is prediction or modeling, see Hire Data Scientists. If the data arrives late or unreliable, see Hire Data Engineers. If the data itself needs to be designed and governed, see Hire Data Architects. If the gap is defining what a system or process has to do, see Hire Business Analysts.

When to hire

When you need a data analyst

The need usually shows up as one of these situations:

Big decisions rest on numbers no one trusts.
Finance, sales, and operations each report a different figure for the same metric, so pricing, budget, and hiring decisions depend on whichever version wins the meeting.
Decisions get made before the data arrives.
Leadership questions wait in a reporting queue, so launches, budgets, and forecasts move ahead on instinct, and the analysis lands when it can only explain the past.
Your data investment isn't paying back.
The company pays for platforms, licenses, and dashboards, yet teams still export to spreadsheets because no one owns the metrics or turns them into answers people use.
A new system went live, and visibility went dark.
After an ERP, CRM, or platform migration, the reports the business ran on stopped working, and leadership is steering revenue, cost, and operations without a clear view.

Need a different role?

If you need someone to predict outcomes or build models, hire a data scientist. If your data arrives late, incomplete, or in the wrong place, hire a data engineer. We recruit for both roles.

Our screen

What our senior data analysts look for

Most candidates can build a dashboard. Fewer can show an analysis that changed a decision, and explain how they knew the numbers were right. A senior data analyst screens every candidate and asks for specifics: the question, the data, the finding, and what the business did with it.

Analysis that changed a decision
We ask for an analysis they delivered and what happened next. A strong data analyst can name the decision it informed, not only the chart.
Checking the data before trusting it
We ask how they caught a data problem before it reached a report, and what they did about it.
Explaining numbers to non-specialists
We ask them to walk through a finding as they would for an executive. Analysts who can't do this produce reports people don't act on.
Fluency with your constraints
A data analyst who has worked with your industry's metrics, your data volume, or regulated data reasons differently from one who hasn't. We weight that context, not only certifications.

Candidates who describe dashboards without the decisions they supported, can't explain how they validated their data, or answer every question with a chart 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 analyst 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 analyst 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 analyst: DevEngine
Time commitment: Full-time, for a defined period
Fits when: A reporting rebuild after a system change, a one-time analysis, or a backlog of requests
Placement protection: Two-week guarantee

Permanent

Who employs the data analyst: You
Time commitment: Full-time, ongoing
Fits when: Reporting and analysis are an ongoing need for one or more teams
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 analyst: DevEngine
Time commitment: Part-time, hourly or monthly
Fits when: A metrics audit, a dashboard cleanup, or a few hours a week of analysis, without a full-time seat
Placement protection: Tailored to the scope of work

	Contract	Permanent	Fractional
Who employs the data analyst	DevEngine	You	DevEngine
Time commitment	Full-time, for a defined period	Full-time, ongoing	Part-time, hourly or monthly
Fits when	A reporting rebuild after a system change, a one-time analysis, or a backlog of requests	Reporting and analysis are an ongoing need for one or more teams	A metrics audit, a dashboard cleanup, or a few hours a week of analysis, 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 analyst search runs

You brief us on the scope and goals of the project, your current data and BI stack, and the stakeholders who will rely on the work.
We source for your role in Canada, Latin America, or the US, not from a bench.
A senior data analyst 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 analyst 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.

FAQ

Data analyst hiring questions

How much does it cost to hire a data analyst?

Cost depends on four things: seniority, industry and data domain, 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 analysts bring?

Most work in SQL, and many use Python or R for deeper analysis, along with the reporting and BI tools your teams already use. Common certifications include the Microsoft Certified: Power BI Data Analyst Associate, the Tableau Certified Data Analyst, and the Google Data Analytics Professional Certificate. Skills and certifications show familiarity, but not whether someone can turn data into a decision. That's what the senior data analyst screen tests.

Can a data analyst work if our data isn't clean or centralized yet?

Yes, up to a point. A data analyst can document what data exists, flag quality problems, and build reliable reporting on top of it. When the data has to be moved, combined, or rebuilt at the source, that work usually needs a data engineer, and we can scope both roles together.

Can I hire a fractional data analyst?

Yes. A fractional data analyst works part-time, on an hourly or monthly cadence, inside your team and tools. Companies often use one for a metrics audit, a dashboard cleanup, or a few hours a week of analysis for leadership. DevEngine places fractional data analysts from Canada, Latin America, and the US.

Should I hire a data analyst 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 analyst work with a DevEngine Engineering POD?

Yes. A data analyst can sit inside an Engineering POD or work alongside one. You choose the POD's composition and direct the work. The data analyst defines the metrics and reporting, and the engineers build the data and features behind 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.

Share your project scope and what it needs to deliver.

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.