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Remote Data Extraction Jobs in Toronto, ON (NOW HIRING)

Mercor

Data Engineer - AI Coding Expert

Toronto, ON · Remote

CA$80/hr

Remote Role Responsibilities * Use frontier AI coding agents to complete and evaluate complex data engineering tasks. * Review model-generated implementations involving ETL pipelines , data ...

Rakuten Kobo

Fraud Lead (12-month contract)

Toronto, ON · On-site +1

Experience with Python, SQL, or other languages used for automation or data extraction * Excellent communication and collaboration abilities The Perks: * Flexible hours and hybrid remote working ...

Lakeview Loan Servicing

Data Engineer

Toronto, ON · Remote

CA$140K - CA$240K/yr

... Remote Qualifications: * 2-4+ years of experience building and operating production-grade data pipelines and data systems * Strong experience with industry-standard tools and platforms for ETL/ELT ...

Fusemachines

Senior Data Engineer

Toronto, ON · Remote

Remote Full-time Senior Data Engineer Are you an experienced Data Engineering professional with a ... Lead the development of ETL/ELT processes for both batch and real-time data processing.

Zenni Optical

Manager, Data Analytics - Canada

Toronto, ON · Remote

CA$300/day

This is a remote role overseeing a team of 2 and reporting to the Sr. Director of Data Engineering ... ETL/ELT pipelines for centralized data warehouses. * Advanced fluency in SQL and Python, with the ...

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All JobsData Extraction JobsRemote Data Extraction JobsRemote Data Extraction Jobs in Toronto, ON

Remote Data Extraction information

What are some common challenges faced in a remote data extraction role and how can they be addressed?

One common challenge in remote data extraction is ensuring data accuracy while working independently, especially when dealing with large and diverse datasets. Discrepancies can arise from inconsistent data formats or sources, so developing strong attention to detail and utilizing reliable extraction tools is critical. Another challenge is communication, as collaborating with data analysts or project managers remotely requires proactive updates and clear documentation. To address these issues, it's helpful to establish regular check-ins with your team, use standardized data templates, and stay organized with project management software.

What jobs pay 4000 a week without a degree?

Remote data extraction roles can pay around $4,000 per week for experienced professionals, especially those skilled in data scraping, automation tools, and programming languages like Python or SQL. These positions often require strong technical skills, self-motivation, and the ability to work independently, with some roles offering high pay based on project complexity and volume.

How to make $1000 a week remotely?

Remote data extraction jobs can pay between $10 and $25 per hour, so earning $1000 weekly typically requires working 40 to 50 hours. Developing strong data handling skills, familiarity with tools like Excel or data scraping software, and maintaining consistent productivity can help achieve this income level. Building a reliable client base or working through reputable platforms can also increase earning potential.

What is remote data extraction?

Remote data extraction is the process of retrieving and collecting data from various sources—such as websites, databases, or documents—without being physically present at the source location. This is typically achieved using specialized software, scripts, or tools that can access and gather data over the internet or through remote connections. Professionals in this field often automate data collection tasks to save time and improve accuracy, especially when dealing with large volumes of information. Remote data extraction is commonly used for business intelligence, market research, competitive analysis, and data migration projects.

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

To thrive as a Remote Data Extraction Specialist, you need proficiency in data analysis, attention to detail, and experience with data extraction and transformation techniques, often supported by a degree in computer science, information systems, or a related field. Familiarity with tools such as SQL, Python, web scraping frameworks (like BeautifulSoup or Scrapy), and data management platforms is typically required. Strong problem-solving skills, self-motivation, and effective communication are valuable soft skills for excelling in a remote environment. These abilities ensure accurate data collection, efficient workflow, and reliable delivery of insights for business or research needs.

How to become a data extractor?

To become a remote data extractor, you should develop skills in data collection, cleaning, and analysis, often using tools like Excel, SQL, or web scraping software. Relevant experience, attention to detail, and the ability to work independently are important, and some roles may require basic knowledge of programming languages such as Python or JavaScript.

What is the difference between Remote Data Extraction vs Remote Data Entry?

AspectRemote Data ExtractionRemote Data Entry
Primary FocusExtracting data from various sources like websites, PDFs, or imagesInputting data into databases or spreadsheets
Skills RequiredWeb scraping, data analysis, attention to detailTyping speed, accuracy, basic computer skills
Tools UsedWeb scraping software, OCR tools, data management platformsExcel, Google Sheets, data entry software
Work EnvironmentMostly independent, often project-basedConsistent, repetitive tasks

Remote Data Extraction involves retrieving data from various sources, requiring technical skills like web scraping and data analysis. Remote Data Entry focuses on inputting data accurately into systems, emphasizing speed and precision. Both roles are remote-friendly but differ in technical complexity and daily tasks.

Is 40 too late for data science?

Age is not a strict barrier for a remote data extraction or data science role; many professionals transition into the field later in life. Success depends on skills, experience, and continuous learning of tools like Python, SQL, and machine learning concepts, regardless of age.
What are popular job titles related to Remote Data Extraction jobs in Toronto, ON? For Remote Data Extraction jobs in Toronto, ON, the most frequently searched job titles are:
What job categories do people searching Remote Data Extraction jobs in Toronto, ON look for? The top searched job categories for Remote Data Extraction jobs in Toronto, ON are:
Remote Data Extraction jobs near you
Infographic showing various Remote Data Extraction job openings in Toronto, ON as of July 2026, with employment types broken down into 1% As Needed, 85% Full Time, 11% Part Time, 1% Temporary, and 2% Contract. Highlights an 87% Physical, 3% Hybrid, and 10% Remote job distribution.

Senior Data Engineer - Machine Learning & Data Platforms - REMOTE

Talent To Hire Inc.

Toronto, ON • Remote

CA$125K - CA$140K/yr

Full-time

Posted 10 hours ago

Job description

🚀 Senior Data Engineer- Machine Learning & Data Platforms | Remote

Our client is building the next generation of industrial intelligence, transforming complex automotive and industrial data into real-time, actionable insights powered by machine learning. This is a FT remote position. You can work from Toronto, Ottawa or Montreal.

We are seeking an experienced Data Engineer who thrives in high-scale, production ML environments and enjoys working with complex, messy datasets to build reliable, scalable data foundations for advanced analytics.

You will join a team of 13 engineers and data professionals, working in a highly collaborative, fast-moving environment. The role is remote-friendly, with strong cross-functional interaction across engineering, data science, and business teams.

🔧 What You’ll Do

  • Design, build, and maintain scalable data pipelines and ETL processes for large structured and unstructured datasets

  • Develop and optimize Spark-based data workflows supporting production ML systems

  • Collaborate closely with data scientists, ML engineers, and business stakeholders

  • Translate complex business needs into scalable, production-grade data solutions

  • Build feature engineering pipelines for time-series and predictive models

  • Ensure data quality, governance, security, and reliability across systems

  • Continuously improve data architecture, performance, and scalability

🧠 What You Bring

  • Min. 6+ years in data engineering or ML data pipeline development

  • Strong experience with Apache Spark, PySpark, Databricks, Delta Lake

  • Advanced skills in Python, SQL, and Airflow

  • Deep understanding of Medallion architecture and ETL design patterns

  • Experience building time-series features (rolling windows, lags, trend indicators)

  • Ability to work closely with ML teams and translate data into model-ready structures

  • Bachelor’s or Master’s in Computer Science, Engineering, or related field

⭐ Preferred Experience - we will highly consider candidates with below skills;

  • Background in retail, e-commerce, or supply chain environments dealing with large, messy, high-volume datasets

  • Experience working directly with machine learning teams or supporting ML model development

  • Hands-on experience in forecasting, demand planning, or similar data-heavy business domains

  • Experience integrating data from ERP/CRM/WMS systems (SAP, Oracle, legacy platforms)

  • Exposure to feature stores or ML training/serving consistency frameworks

  • Experience with IBM DataStage or legacy ETL modernization projects

  • Experience scaling distributed ML or time-series models in production environments

🌍 Why This Role

This is a strong fit for someone who enjoys working in complex, real-world data environments, especially with messy, high-volume retail-style data and close collaboration with ML teams. Retail or similar domains are highly valued.

APPLY: sasha@talenttohire.com