ZipRecruiter

Log In

1

Data Analyst Jobs in Manitoba (NOW HIRING)

Sapsol Technologies Inc

Data Analyst

Winnipeg, MB · On-site

Analyze legacy PHP applications with embedded SQL to understand system logic * Reverse engineer reports to identify data sources, dependencies, and requirements * Develop SQL queries and data ...

Ellement Consulting Group

Pension Analyst

Winnipeg, MB · On-site

Quality control of year-end data input and verification of program output, including Annual Benefit ... Strong analytical, mathematical, and problem-solving skills. * Proficient working knowledge of ...

All JobsData Analyst JobsData Analyst Jobs in Manitoba

Data Analyst information

See Manitoba salary details

$12

$34

$59

How much do data analyst jobs pay per hour?

As of Sep 3, 2026, the average hourly pay for data analyst in Manitoba is $34.15, according to ZipRecruiter salary data. Most workers in this role earn between $24.52 and $40.87 per hour, depending on experience, location, and employer.

What does a data analyst do?

A Data Analyst is responsible for collecting, processing, and analyzing data to help organizations make informed business decisions. They use statistical tools and software to interpret data sets, identify trends, and create visual reports. Data Analysts often collaborate with other departments to provide actionable insights and support strategic planning. Their work helps organizations optimize operations, track performance, and solve business problems using data-driven approaches.

What are the key skills and qualifications needed to thrive as a data analyst, and why are they important?

To thrive as a Data Analyst, you need strong analytical skills, proficiency in statistics, and a relevant degree such as in mathematics, statistics, or computer science. Familiarity with data analysis tools like SQL, Excel, Python or R, and experience with visualization platforms such as Tableau or Power BI are typically required. Strong problem-solving abilities, attention to detail, and effective communication skills help analysts interpret data insights and present findings clearly to stakeholders. These skills are crucial for transforming raw data into actionable business insights that drive informed decision-making.

What are some common challenges data analysts face when working with large datasets, and how are they typically addressed?

Data Analysts often encounter challenges such as data quality issues, missing or inconsistent values, and slow processing times when handling large datasets. These challenges are typically addressed by implementing data cleaning routines, using advanced data management tools, and leveraging programming languages like Python or R for efficient data manipulation. Collaboration with database administrators and IT teams is also common to ensure data integrity and optimize data storage solutions. Staying updated with best practices in data wrangling and visualization helps Data Analysts deliver accurate and actionable insights.

What is the difference between Data Analyst vs Data Scientist?

AspectData AnalystData Scientist
Required CredentialsBachelor's degree in statistics, mathematics, or related field; often certifications in data analysis toolsBachelor's or master's in computer science, statistics, or related; often advanced certifications or degrees
Work EnvironmentBusiness settings, focusing on data reporting and visualizationResearch and development environments, focusing on predictive modeling and complex algorithms
Employer & Industry UsageRetail, finance, healthcare, and marketing companiesTech firms, research institutions, and large enterprises

While both roles analyze data, Data Analysts primarily focus on interpreting existing data to generate reports and insights, whereas Data Scientists develop predictive models and advanced algorithms to forecast trends and solve complex problems.

Do data analysts get paid well?

Data analysts typically earn competitive salaries that vary by experience, location, and industry. Entry-level positions may start lower, but with skills in tools like Excel, SQL, and data visualization, salaries tend to increase with expertise and certifications. Overall, data analysis is considered a well-paying field with growth potential.

Is it hard to get a data analyst job?

Securing a data analyst position can be competitive, as it often requires strong skills in data manipulation, statistical analysis, and proficiency with tools like Excel, SQL, or Python. Candidates with relevant education, certifications, and experience tend to have better chances, but persistence and continuous skill development are important.

What work does a data analyst do?

A data analyst collects, processes, and analyzes large datasets to identify trends, patterns, and insights that support business decision-making. They use tools like Excel, SQL, and data visualization software to interpret data and communicate findings to stakeholders. Strong analytical skills and attention to detail are essential for this role.
More about Data Analyst jobs

What are the most commonly searched types of Data Analyst jobs in Manitoba?

The most popular types of Data Analyst jobs in Manitoba are:

What are popular job titles related to Data Analyst jobs in Manitoba?

For Data Analyst jobs in Manitoba, the most frequently searched job titles are:

What job categories do people searching Data Analyst jobs in Manitoba look for?

The top searched job categories for Data Analyst jobs in Manitoba are:

What cities in Manitoba are hiring for Data Analyst jobs?

Cities in Manitoba with the most Data Analyst job openings:

Data Analyst jobs near you
Infographic showing various Data Analyst job openings in Manitoba as of August 2026, with employment types broken down into 1% As Needed, 84% Full Time, 12% Part Time, and 3% Contract. Highlights an 82% Physical, 3% Hybrid, and 15% Remote job distribution, with an average salary of $71,034 per year, or $34.2 per hour.

Data Analyst

Sapsol Technologies Inc

Winnipeg, MB • On-site

Contractor

Re-posted 9 days ago

Job description

You will support a critical operational reporting and data initiative within a university environment. This role focuses on modernizing legacy reporting systems, improving data access, and enabling better decision-making across faculties and departments.

Responsibilities

  • Analyze legacy PHP applications with embedded SQL to understand system logic
  • Reverse engineer reports to identify data sources, dependencies, and requirements
  • Develop SQL queries and data extracts to support reporting needs
  • Redesign and migrate reports to new data sources (Data Warehouse/Data Lake)
  • Build and enhance PHP applications with supporting JavaScript
  • Document data structures, workflows, and reporting logic
  • Collaborate with stakeholders to validate business requirements
  • Perform data validation and testing to ensure accuracy and performance
  • Produce migration specifications and technical documentation
  • Support deployment and transition of reports to production

Apply