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Remote Data Analyst Jobs in Alberta (NOW HIRING)

Olsen Consulting

Senior Data Analyst

Calgary, AB · On-site +1

Senior Data Analyst Olsen Consulting specializes in the implementation and optimization of ... high-performance - Remote work flexibility, allowing you to optimize your work-life balance ...

emergiTEL Inc.

Data Architect - Senior

Edmonton, AB · Remote

Remote within Canada (Occasional Edmonton onsite meetings - approximately 15%) Contract Type ... Perform detailed data profiling and analysis. * Develop data architecture designs, mappings, and ...

Targeted Talent

Data Scientist

Calgary, AB · Remote

This is a permanent position that is completely remote! Our client is a fintech company based out ... Strong analytical skills working with unstructured data sets * Knowledge of relational (PostgreSQL ...

Targeted Talent

Data Scientist

Calgary, AB · Remote

This is a permanent position that is completely remote! Our client is a fintech company based out ... Strong analytical skills working with unstructured data sets * Knowledge of relational (PostgreSQL ...

Targeted Talent

Data Scientist

Edmonton, AB · Remote

This is a permanent position that is completely remote! Our client is a fintech company based out ... Strong analytical skills working with unstructured data sets * Knowledge of relational (PostgreSQL ...

Targeted Talent

Data Scientist

Edmonton, AB · Remote

This is a permanent position that is completely remote! Our client is a fintech company based out ... Strong analytical skills working with unstructured data sets * Knowledge of relational (PostgreSQL ...

Targeted Talent

Senior Data Scientist

Edmonton, AB · Remote

This is a permanent position that is completely remote! Our client is a fintech company based out ... Strong analytical skills working with unstructured data sets * Knowledge of relational (PostgreSQL ...

Targeted Talent

Senior Data Scientist

Calgary, AB · Remote

This is a permanent position that is completely remote! Our client is a fintech company based out ... Strong analytical skills working with unstructured data sets * Knowledge of relational (PostgreSQL ...

Targeted Talent

Senior Data Scientist

Edmonton, AB · Remote

This is a permanent position that is completely remote! Our client is a fintech company based out ... Strong analytical skills working with unstructured data sets * Knowledge of relational (PostgreSQL ...

Targeted Talent

Senior Data Scientist

Calgary, AB · Remote

This is a permanent position that is completely remote! Our client is a fintech company based out ... Strong analytical skills working with unstructured data sets * Knowledge of relational (PostgreSQL ...

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All JobsRemote Data Analyst JobsRemote Data Analyst Jobs in Alberta

Remote Data Analyst information

See Alberta salary details

$11

$40

$69

How much do remote data analyst jobs pay per hour?

As of Jun 17, 2026, the average hourly pay for remote data analyst in Alberta is $40.90, according to ZipRecruiter salary data. Most workers in this role earn between $26.20 and $57.69 per hour, depending on experience, location, and employer.

What are the key skills and qualifications needed to thrive as a Remote Data Analyst, and why are they important?

To thrive as a Remote Data Analyst, you need strong analytical skills, proficiency in statistics, and a degree in a quantitative field such as mathematics, statistics, or computer science. Familiarity with data analysis tools like SQL, Excel, Python or R, and visualization platforms such as Tableau or Power BI is typically required. Excellent communication, self-motivation, and time management are crucial soft skills for collaborating remotely and presenting insights effectively. These skills ensure accurate data-driven decision-making and effective remote teamwork in a digital work environment.

Can I do a data analyst job remotely?

Yes, many data analyst positions are available as remote jobs, allowing professionals to work from anywhere with a computer and internet connection. Remote data analysts often use tools like Excel, SQL, and data visualization software, and strong communication skills are important for remote collaboration.

Is 40 too late for data science?

For a remote data analyst role, age is generally not a barrier; many professionals transition into data science or analytics later in their careers. Success depends on acquiring relevant skills such as programming, statistics, and tools like SQL or Python, regardless of age. Continuous learning and building a strong portfolio can help late entrants compete effectively in the field.

How do Remote Data Analysts typically collaborate with team members and stakeholders given the virtual work environment?

Remote Data Analysts often rely on digital communication tools such as Slack, Microsoft Teams, and Zoom to stay connected with colleagues and stakeholders. They participate in regular virtual meetings, share dashboards or reports via cloud-based platforms, and provide data-driven insights to support decision-making. Successful remote analysts proactively communicate their findings, clarify requirements, and coordinate with cross-functional teams such as IT, marketing, or finance to ensure alignment on project goals and deliverables.

Is AI replacing data analysts?

AI tools are automating certain data processing tasks, but data analysts are still essential for interpreting complex data, making strategic decisions, and providing context. The role of a remote data analyst involves skills in data visualization, statistical analysis, and tools like SQL and Python, which complement AI capabilities rather than being replaced by them.

What does a Remote Data Analyst do?

A Remote Data Analyst is responsible for collecting, processing, and analyzing data to help organizations make informed business decisions, all while working from a location outside of a traditional office. They use statistical tools and software to interpret complex datasets, identify trends, and generate reports. Remote Data Analysts collaborate with team members via digital communication platforms and often present their findings to stakeholders to guide strategy and operations. Their work is essential in industries such as finance, healthcare, marketing, and technology, where data-driven decisions are crucial.

What is the difference between Remote Data Analyst vs Remote Data Scientist?

AspectRemote Data AnalystRemote Data Scientist
Required CredentialsBachelor's in Data, Statistics, or related field; often certifications in Excel, SQL, or TableauBachelor's or Master's in Data Science, Computer Science, or related; certifications in Python, R, machine learning
Work EnvironmentPrimarily office-based or remote, focusing on data analysis and reportingPrimarily remote, involving complex data modeling and predictive analytics
Employer & Industry UsageUsed across finance, marketing, healthcare, and retail sectorsCommon in tech, finance, and research industries

Remote Data Analysts focus on interpreting data, creating reports, and supporting decision-making, while Remote Data Scientists develop models, perform advanced analytics, and work on predictive insights. Both roles require strong analytical skills, but Data Scientists typically have more technical expertise in programming and machine learning.

What jobs pay 200,000 a year in the USA?

Remote Data Analysts typically do not reach $200,000 annually, but senior data analyst roles with extensive experience, advanced skills in SQL, Python, or R, and industry certifications can approach or exceed this level. High-paying data-related roles often involve leadership, specialized expertise, or working in industries like finance or technology. Executive or specialized data science positions are more likely to offer salaries at or above this threshold.

What Does a Remote Data Analyst Do?

Remote data analysts use a range of methods to chart, examine, and analyze data for their clients. Unlike in-house data analysts, remote data analysts, work from home or a different location outside of the office. As a remote data analyst, your job is to evaluate a company’s data using a combination of mathematical inspection, transformation, and modeling techniques to simplify and condense it. Once the analysis is complete, you create reports for management to use to make critical decisions; this is why remote data analysts need to confirm the accuracy of the data. You may also need to present your reports to stakeholders.

More about Remote Data Analyst jobs
What are the most commonly searched types of Data Analyst jobs in Alberta? The most popular types of Data Analyst jobs in Alberta are:
What are popular job titles related to Remote Data Analyst jobs in Alberta? For Remote Data Analyst jobs in Alberta, the most frequently searched job titles are:
What job categories do people searching Remote Data Analyst jobs in Alberta look for? The top searched job categories for Remote Data Analyst jobs in Alberta are:
Remote Data Analyst jobs near you

Data Analyst (Remote) JP927

P@thlion Staffing Careers

Edmonton, AB • Remote

Full-time

Posted 27 days ago

Job description

Project Name:
Digital Regulatory Assurance System
Job Title: Data Product Analyst
Scope:
The Data Product Analyst – Intermediate will primarily support the Digital Regulatory Assurance System (DRAS) program, where high quality, timely analytics are essential to regulatory and compliance functions. As data and analytics maturity increases, the role may be expanded to support additional enterprise data initiatives.
Modernization initiatives across the Government of Alberta are fundamentally changing how ministry users collect, manage, analyze, and use data as legacy systems are transformed into modern Data Management and Geospatial Platforms. This shift requires dedicated analytical capacity to ensure that the value of modernized data assets is fully realized.
DRAS is a Government of Alberta regulatory transformation initiative led by Environment and Protected Areas (EPA) to modernize, digitize, and streamline environmental and natural resource regulatory processes. DRAS supports the full regulatory lifecycle, from application and authorization to monitoring, compliance, remediation, and closure through a single, consolidated digital platform
As DRAS development continues, the volume, variety, and complexity of structured data continue to grow, creating a sustained need for dedicated data engineering and data product expertise. The Data Product Analyst role is critical to ensuring that modernization delivers tangible business value. This role will design, build, and operate reliable data pipelines that ingest and integrate data into the DMP, apply standardized transformations, enforce data quality and governance controls, and produce trusted, analytics‑ready datasets that support regulatory oversight, compliance monitoring, and evidence‑based decision‑making aligned with DRAS objectives.
Duties:
Design and implement scalable, secure, and high-performance data architecture on Microsoft Azure, supporting both cloud-native and hybrid environments.
Lead the development of data ingestion, transformation, and integration pipelines using Azure Data Factory, Azure Databricks, and Azure Synapse Analytics.
Work with the Data Architect and manage data lakes and structured storage solutions using Azure Data Lake Storage Gen2, ensuring efficient access and governance.
Integrate data from diverse source systems including ServiceNow, and geospatial systems, using APIs, connectors, and custom scripts.
Develop and maintain robust data models and semantic layers to support operational reporting, analytics, and machine learning use cases.
Build and optimize data workflows using Python and SQL for data cleansing, enrichment, and advanced analytics within Azure Databricks.
Design and expose secure data services and APIs using Azure API Management for downstream systems.
Implement data governance practices, including metadata management, data classification, and lineage tracking.
Ensure compliance with privacy and regulatory standards (e.g., FOIP, GDPR) through role-based access controls, encryption, and data masking.
Monitor and troubleshoot data pipelines and integrations, ensuring reliability, scalability, and performance across the platform.
Utilize AI and automation tools to streamline data engineering workflows, including pipeline development, testing, monitoring, and documentation.
Leverage AI-assisted tools for code generation, optimization, and review to improve development efficiency and code quality.
Design and curate standardized, high‑quality datasets that are suitable for advanced analytics and future AI use cases.