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Data Extraction Jobs in Ontario (NOW HIRING)

Reconomy

Extract and consolidate data from multiple systems using SQL and other data access tools. * Design and implement standardized data models across key business processes and financial metrics.

Ci

Data Engineer

Toronto, ON · On-site

CA$69K - CA$119K/yr

Design, develop, and help maintain data assets to extract, transform, and load data from various internal and external data files, APIs, and databases, and to make them accessible to various client ...

Konrad

Data Engineer

Toronto, ON · Hybrid

CA$90K - CA$125K/yr

Perform data modelling, data extraction, transformation, and loading (ETL/ELT). * Identify and recommend innovative solutions to enhance data quality and analytics capabilities. Qualifications

Scotiabank

Data Engineer

Toronto, ON

Experience with data engineering, programming, ETL and ELT processes for data extraction and processing * Experience working with structured, semi-structured, and unstructured data. * Strong ...

Scotiabank

Data Engineer

Toronto, ON

Experience with data engineering, programming, ETL and ELT processes for data extraction and processing * Experience working with structured, semi-structured, and unstructured data. * Strong ...

Scotiabank

Data Scientist - AI/ML

Toronto, ON

Develop, test, and implement highly effective models optimized for specific document understanding tasks (e.g., data extraction, classification). * Write and maintain high-quality Python code to ...

Ci

Senior Data Engineer

Toronto, ON · On-site

CA$69K - CA$119K/yr

Design, develop, and maintain data assets to enable seamless extraction, transformation, and loading (ETL/ELT) processes from diverse data sources, making data accessible to client-facing ...

The City of Guelph

Data Analyst (Transit)

Guelph, ON · Hybrid

CA$77K - CA$96K/yr

Extract, transform, analyze, and integrate data from multiple transit and enterprise systems, including scheduling, fare, operational, ERP, AVL, APC, and GIS platforms. * Deliver ad hoc analysis and ...

Ci

Data Operations Specialist

Toronto, ON · On-site

CA$69K - CA$119K/yr

Data extraction - SQL, Python, API invocation, CDC * Data storage repositories - SFTP, AWS S3 * ETL/ ELT tools and workflow - Snowpipe, PySpark, AWS Glue, EMR, AWS Lambda, SCD * A strong analytical ...

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All JobsData Extraction JobsData Extraction Jobs in Ontario

Data Extraction information

See Ontario salary details

$11

$28

$69

How much do data extraction jobs pay per hour?

As of Jul 26, 2026, the average hourly pay for data extraction in Ontario is $28.18, according to ZipRecruiter salary data. Most workers in this role earn between $15.14 and $31.25 per hour, depending on experience, location, and employer.

What are the typical daily responsibilities for someone working in Data Extraction?

Professionals in Data Extraction typically spend their days gathering data from a variety of sources—such as databases, websites, or documents—using specialized tools or scripts. They are responsible for cleaning, formatting, and validating this data to ensure accuracy and consistency before delivering it to analysts or other stakeholders. Collaborating with data analysts, IT teams, and business units is common to clarify data requirements and resolve any discrepancies. Most roles involve a mix of independent technical work and teamwork, with some positions requiring regular reporting or documentation of data extraction processes.

How to become a data extractor?

To become a data extractor, you typically need strong skills in data management, familiarity with data extraction tools like SQL, Python, or specialized software, and attention to detail. Many roles require a high school diploma or higher, and some may prefer certifications in data analysis or related fields. Gaining experience through internships or entry-level positions can also help build relevant skills.

What are the key skills and qualifications needed to thrive in the Data Extraction position, and why are they important?

To excel in Data Extraction, candidates should have strong analytical skills, attention to detail, and a background in data management or computer science. Experience with extraction tools and programming languages such as SQL, Python, R, or ETL platforms, as well as familiarity with data governance standards, is often required. Strong organizational, problem-solving, and communication skills help professionals handle complex datasets and collaborate effectively across teams. These competencies ensure accurate, efficient data retrieval and support informed business decisions.

What is a Data Extraction job?

A Data Extraction job involves collecting and retrieving data from various sources, such as databases, documents, websites, and APIs. This data is then transformed, cleaned, and structured for analysis or storage. Professionals in this role use tools like SQL, Python, or web scraping technologies to automate the process. Data extraction is essential for businesses to gain insights, make data-driven decisions, and streamline operations.

What is a data extraction job?

A data extraction job involves retrieving specific information from various sources such as websites, databases, or documents. It often requires skills in using tools like web scrapers or data management software and may involve cleaning and organizing data for analysis or reporting.

What does a data extractor do?

A data extractor is responsible for collecting and retrieving data from various sources such as websites, databases, or documents. They often use tools like web scraping software or data management systems and need strong attention to detail and technical skills. The role involves transforming unstructured data into organized formats for analysis or storage.
What are popular job titles related to Data Extraction jobs in Ontario? For Data Extraction jobs in Ontario, the most frequently searched job titles are:
What job categories do people searching Data Extraction jobs in Ontario look for? The top searched job categories for Data Extraction jobs in Ontario are:
Data Extraction jobs near you
Infographic showing various Data Extraction job openings in Ontario as of July 2026, with employment types broken down into 85% Full Time, and 15% Contract. Highlights an 90% In-person, 5% Hybrid, and 5% Remote job distribution, with an average salary of $58,613 per year, or $28.2 per hour.

RQ10972 - Data Analytical Specialist/Scientist - Intermediate

Flexstaf IT

Toronto, ON

Full-time

Posted 15 hours ago

Job description

Must Have:

Key Requirements for a Data Specialist / Analytics Role

  • Strong data analysis and problem-solving skills
  • Advanced proficiency in SQL for data extraction, transformation, and analysis
  • Expertise in Power BI dashboard and report development
  • Ability to design and develop interactive Power BI dashboards, scorecards, and KPI reports
  • Strong knowledge of DAX and Power Query for advanced analytics and data transformation
  • Experience with data modeling (fact and dimension tables, star schema)
  • Data cleansing, validation, and quality management
  • Experience with ETL processes and data integration from multiple sources
  • Ability to gather business requirements and translate them into reporting solutions
  • Strong data visualization and storytelling skills
  • Experience creating executive, operational, and analytical reports
  • Knowledge of Power BI Service, report publishing, workspace management, and security
  • Understanding of Row-Level Security (RLS) and data governance practices
  • Experience working with large datasets and data warehouses
  • Familiarity with cloud analytics platforms and modern data ecosystems
  • Ability to identify trends, patterns, risks, and opportunities through data analysis
  • Strong stakeholder communication and presentation skills
  • Experience documenting data definitions, KPIs, and reporting processes
Core Technical Skills
  • Power BI Dashboard & Report Development
  • DAX
  • Power Query (M)
  • SQL
  • Data Modeling
  • Data Visualization
  • ETL & Data Integration
  • KPI & Performance Reporting
  • Data Quality Management
  • Power BI Service & RLS

Nice to have:

Prior OPS or Public sector Exp.


Experience and Skill Set Requirements

Responsibilities:

  • Lead the development and delivery of functional and ministry-specific analytics to support evidence-based decision-making and produce actionable insights
  • Work closely with client's groups to assess current data analytics and reporting capabilities, gather future-state requirements and identify further opportunities for improvement
  • Facilitate decision-making and manage client expectations
  • Own the execution of analytics initiatives including end-to-end reporting and data set delivery
  • Develop robust statistical models and machine learning algorithms to model business scenarios and extract valid inferences
  • Participate in documentation, development, testing, and end user training
  • Work with functional area experts, Data Architects and ETL Developers and stakeholders to understand complex business issues and develop appropriate Business Intelligence solutions
  • Assist the Lead Developers with ETL and/or SSIS development where necessary
  • Design methods to capture, structure, transform, and process data to be used to generate models
  • Build data models that provide information which is accurate, easy to understand and unbiased
  • Communicate complex quantitative analysis in a clear and precise manner, providing useful visuals and summaries
  • Provide interpretation, advice, and expertise to client groups and other stakeholders, including direction on how to transform analytics into actionable information and proactive insights that support decision making

General Skills:

  • Excellent analytical, problem-solving and decision-making skills, verbal and written communication skills, interpersonal skills and team work skills
  • Outstanding consulting and relationship management skills, with proven ability to elicit requirements, develop/consult on options and solutions, and provide effective guidance
  • Adept at communicating to both technical and non-technical audiences
  • Experience with a range of analytical methods, techniques and tools such as, but not limited to: statistical analysis and modelling, data mining, machine learning and algorithms, natural language processing, and other related disciplines at the specified experience level
  • Ability to manipulate and analyze complex, high-volume data from structured and unstructured sources
  • Experience developing data extraction, transformation, and load functionality for large relational and multi-dimensional data stores
  • Experience designing high quality interfaces to present information in a meaningful way to end users
  • Broad understanding of data management, financial and business analysis, database architecture, and information visualization
  • Proficiency in query languages and experience constructing complex query statements
  • Experience in one or more programming or scripting languages
  • Strong investigative and logic skills
  • Proficiency in mathematics and statistics
  • Awareness of emerging Business Intelligence trends and directions

Knowledge Transfer

  • Knowledge Transfer should be done to designated technical cluster FTE.
  • Knowledge transfer must be completed two weeks prior to the consultant leaving the ministry.
  • All deliverables, including design/supporting/release/training documents must be checked into designated version control repositories (for example, SharePoint, DevOps).
  • All final documents and working drafts related to project requirements or business analysis or solution design or solution development or QA testing plans or Architectural artefacts and other working related documents must be stored on designated project SharePoint folder and Azure DevOps.
  • Project manager and designated FTE must be regularly informed in writing (by email) of where documentation has been stored and must be provided a minimum of one walk-through of all documentation as part of the final knowledge transfer activities.
  • Knowledge will be transferred through 1 on 1 sessions, emails, document updates and document review with the team.

Experience and Skill Set Requirements

Tools and techniques - 40%

  • Experience with a range of analytical methods, techniques and tools such as statistical analysis and modelling, data mining, machine learning and algorithms, natural language processing, and other related disciplines
  • Experience building visualizations in R, R Shiny, PowerBI, or other tools
  • Experience with ETL and SSIS development
  • Experience with scripting such as Python, and languages such as DAX to be able to do trend analysis
  • Experience in Microsoft technology stack, including Azure Data Factory, SSIS, SSAS, SSRS, Power BI, and supporting tools like Visual Studio and SQL Server Management Studio.

BI and Analytics Experience - 40%

  • Experience developing BI and analytics
  • Experience with creating dashboards and data visualization via Power BI Server (On-Prem) and Power BI Services (Cloud) or other visualization tools
  • Experience with cleaning, transforming and visualizing data sets
  • Advanced experience with SQL
  • Demonstrated knowledge of emerging Business Intelligence trends and directions
  • Experience with dimensional data/building cubes

Soft Skills - 15%

  • Outstanding consulting and relationship management skills, with proven ability to elicit requirements, develop/consult on options and solutions, and provide effective guidance
  • Strong verbal and written communication skills; with both technical and non-technical audiences
  • Excellent analytical, problem-solving and decision-making skills
  • Strong leadership and collaboration skills
  • Proven track record for building strong working relationships
  • A demonstrated team player with a track record for meeting deadlines

Public Sector Experience - 5%

  • Previous public sector experience in an organization of equivalent size or complexity in Public Service
  • Demonstrates experience designing and developing applications that comply with GOITS standards and general processes would be an asset.