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Data Analyst Jobs in Calgary, AB (NOW HIRING)

Data Elephant Inc

Oracle Data Analyst

Calgary, AB · Remote

Senior Oracle Data Analyst - Contract We are seeking a senior Oracle Data Analyst to support a major application and database modernization initiative within the oil and gas sector. This is an ...

New

Strathcona Resources Ltd

Data Analyst

Calgary, AB · On-site

We are seeking a skilled Contract Data Analyst to join our Analytics team in Calgary for an 18-month term. Reporting to the Team Lead, Analytics, you will work closely with internal stakeholders and ...

hireVouch

Cloud Data Analyst/ DBA

Calgary, AB · On-site

Strong SQL and data analysis capabilities across relational database platforms. * Experience optimizing queries, indexes, and workloads for cloud-hosted databases. * Knowledge of Azure SQL, Azure ...

Capital Power

Sr. Analyst, Market Data

Calgary, AB · On-site

The Sr. Analyst, Market Data owns Capital Power's end-to-end price curve framework within the Risk Group. The role is accountable for the quality, integrity, and governance of all priceand market ...

All JobsData Analyst JobsData Analyst Jobs in Calgary, AB

Data Analyst information

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.

Can I learn a data analyst in 3 months?

A data analyst role requires skills in data manipulation, statistics, and tools like Excel, SQL, and Python or R. While three months can provide a foundational understanding through intensive training or bootcamps, gaining proficiency typically takes longer with consistent practice and real-world experience.

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 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.

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 top 3 skills for a data analyst?

The top three skills for a data analyst are proficiency in data manipulation and analysis tools like Excel, SQL, and statistical software; strong analytical and problem-solving abilities; and effective communication skills to present insights clearly. Familiarity with data visualization tools such as Tableau or Power BI is also highly valuable. These skills enable data analysts to interpret complex data and support decision-making processes.

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.
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What are popular job titles related to Data Analyst jobs in Calgary, AB? For Data Analyst jobs in Calgary, AB, the most frequently searched job titles are:
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Data Analyst jobs near you
Infographic showing various Data Analyst job openings in Calgary, AB as of August 2026, with employment types broken down into 100% Full Time. Highlights an 100% In-person job distribution.

Oracle Data Analyst

Data Elephant Inc

Calgary, AB • Remote

Contractor

Posted 3 days ago

New

Job description

Senior Oracle Data Analyst - Contract

We are seeking a senior Oracle Data Analyst to support a major application and database modernization initiative within the oil and gas sector. This is an initial 4-6-month contract focused on analyzing and resolving significant data discrepancies between a legacy Oracle application and its newly rebuilt replacement.


The organization is migrating data from multiple source systems into a new Oracle database while improving data transformation, prioritization, and master data management practices. Although the new environment is intended to become the authoritative source, millions of records currently do not align with the legacy system. The immediate priority is understanding why these differences exist and determining how the data should be populated.

This role is primarily analytical rather than development-focused. You will investigate data, trace legacy business rules, review SQL and PL/SQL logic, and identify whether discrepancies are caused by source data, data quality issues, transformation logic, field-mapping rules, or differences between the old and new applications.


Key responsibilities

  • Compare and reconcile large datasets across legacy and new Oracle databases.
  • Investigate approximately 7-10 million identified data discrepancies.
  • Perform detailed root-cause analysis to determine why records and fields do not match.
  • Review Oracle SQL, PL/SQL, stored procedures, and legacy application logic.
  • Trace data from multiple source systems through Informatica and PL/SQL transformations.
  • Determine the intended business rules and how individual fields should be populated.
  • Distinguish between source-data issues, transformation defects, mapping gaps, and logic differences.
  • Document findings, business rules, discrepancy patterns, and recommended resolutions.
  • Work closely with business stakeholders to validate data expectations.
  • Collaborate with architects and developers to recommend fixes that will not negatively affect other processes.
  • Support developers during remediation and validate that implemented fixes resolve the underlying issues.
  • Use AI-assisted analysis tools, where appropriate, to accelerate code review and discrepancy investigation.
  • Work independently, take ownership of assigned analysis, and communicate findings clearly to technical and business audiences.


Required qualifications

  • At least seven years of experience in data analysis, data migration, data quality, database development, or a closely related field.
  • Strong hands-on expertise with Oracle databases, Oracle SQL, and PL/SQL.
  • Demonstrated experience with large-scale data reconciliation, validation, and root-cause analysis.
  • Ability to read and understand existing database code, stored procedures, transformations, and business logic.
  • Experience investigating discrepancies between legacy and modernized systems.
  • Good understanding of ETL processes, relational databases, data warehousing, and data integration.
  • Experience translating technical findings into clear, business-friendly language.
  • Strong analytical skills, attention to detail, and a structured approach to problem-solving.
  • Ability to work with limited direction and take ownership of deliverables.
  • Previous oil and gas industry experience.


Preferred qualifications

  • Experience with Informatica.
  • Exposure to master data management and data governance.
  • Experience working with data originating from multiple operational source systems.
  • Backend application development experience.
  • Familiarity with AI tools such as GitHub Copilot or similar tools for SQL, code, and data analysis.
  • Advanced Excel skills.
  • Experience working within Agile delivery teams.


Contract details

  • Initial duration: 4-6 months
  • Work arrangement: Remote work is acceptable; alignment with the client's working time zone is preferred (MST)
  • Primary focus: Data analysis, reconciliation, and root-cause investigation
  • Industry: Oil and gas



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