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

... remote) Job Overview As a Senior Data Developer, you will be responsible for building and ... Build and productionize modular and scalable data ELT/ETL pipelines and data infrastructure ...

Our team is 100% distributed and remote. Responsibilities: * Design, build, and evolve the core ... Familiarity with reverse ETL tooling (Hightouch) * Familiarity with data catalog and lineage ...

MP4, $80- $95/hr INC Duration: 12 Months Hours of work: 35 Location: (Hybrid - 1 day remote) Temp ... Data Engineering: Build and maintain ETL pipelines using Python to collect, transform, and ...

Remote Duration: Minimum four weeks Commitment: 10+ hours/week Role Responsibilities * Analyze and ... Provide structured feedback to AI research teams to improve training data quality. * Collaborate ...

Senior Marketing Cloud Developer

Toronto, ON · On-site +1

CA$95K - CA$113K/yr

You will partner across marketing, data, and technology teams to deliver measurable business ... You will be based in our Etobicoke office, balancing in-office collaboration with remote ...

Remote Role Responsibilities * Red team conversational AI models and agents. Conduct jailbreaks ... Generate high-quality human data. Annotate failures, classify vulnerabilities, and flag systemic ...

AI Safety Expert - Red Team

Toronto, ON · Remote

CA$20 - CA$22/hr

Contract Compensation: $20-$22/hour Location: Remote Role Responsibilities * Red team ... Generate high-quality human data by annotating failures, classifying vulnerabilities, and flagging ...

... part of our remote team and our mission to elevate the human experience of sexuality and ... Experience implementing and managing integrations, APIs, ETL workflows, and marketing data ...

... part of our remote team and our mission to elevate the human experience of sexuality and ... Experience implementing and managing integrations, APIs, ETL workflows, and marketing data ...

AI Safety Expert - Red Team

Toronto, ON · Remote

CA$29 - CA$45/hr

Remote Role Responsibilities * Red team conversational AI models and agents by performing ... Generate high-quality human data by annotating failures, classifying vulnerabilities, and flagging ...

Showing results 21-40

Remote Data Extraction information

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?

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.

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 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.

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:

Infographic showing various Remote Data Extraction job openings in Toronto, ON as of August 2026, with employment types broken down into 91% Full Time, and 9% Contract. Highlights an 100% Remote job distribution.

26-064 - Staff Data Engineer / Data Architect (Azure / Databricks)

Morson Talent

Oshawa, ON • On-site, Remote

$90 - $100/hr

Full-time

Re-posted 8 days ago


Job description

Job Description Title: Staff Data Engineer / Data Architect (Azure / Databricks) 26-064 Resume Due Date: Wednesday June 17th, 2026 (5:00PM EST) Number of Vacancies: 2 Level: $90- $100/hr INC Duration: 12 Months Hours of work: 35 hours Location: 1908 Colonel Sam Drive (Hybrid - 3 days remote) Job Overview As a Staff Data Engineer/Data Architect, you will be responsible for leading the architecture, design and delivery of scalable data pipelines and data products which enable innovative, customer-centric digital experiences. You will be working as part of a cross-discipline agile team who helps each other solve problems across all business areas. You will be a thought leader and subject matter expert on the data lakehouse, data warehousing and modeling activities for the team and use your influence to ensure that the team produces best-in-class data solutions that leverage repeatable, maintainable, and well-documented design patterns.

You will employ best practice in development, security, accessibility and design to achieve the highest quality of service for our customers. Lead the architecture, design and oversee implementation of modular and scalable data ELT/ETL pipelines and data infrastructure leveraging the wide range of data sources across the organization Design curated common data models that offer an integrated, business-centric single source of truth for business intelligence, reporting, and downstream system use Work closely with infrastructure and cyber teams to ensure data is secure in transit and at rest Create, guide and enforce code templates for delivery of data pipelines and transformations for structured, semi-structured and unstructured data sets Develop modeling guidelines that ensure model extensibility and reuse by employing industry standard disciplines for building facts, dimensions, bridge, aggregates, slowly changing dimensions and other dimensional and fact optimizations Establish standards database system fields, including primary and natural key combinations that optimize join performance in a multi-domain, multiple subject area physical (structured zone) and semantic model (curated zone) Ensure model extensibility by employing industry standard disciplines for building facts, dimensions, bridge, aggregates, slowly changing dimensions and other dimensional and fact optimizations Transform data and map to more valuable and understandable semantic layer sets for consumption, transitioning from system-centric language to business-centric language Collaborate with business analysts, data scientists, data engineers, data analysts and solution architects to develop data pipelines to feed our data marketplace Introduce new technologies to the environment through research and POCs, and prepare POC code designs that can be implemented and productionized by developers Work with tools in the Microsoft Stack; Azure Data Factory, Azure Data Lake, Azure SQL Databases, Azure Data Warehouse, Azure Synapse Analytics Services, Azure Databricks, Microsoft Purview, and Power BI Work within the agile SCRUM work management framework in delivery of products and services, including contributing to feature & user story backlog item development, and utilizing related Kanban/SCRUM toolsets Document as-built architecture and designs within the product description Design data solutions that enable batch, near-real-time, event-driven, and/or streaming approaches depending on business requirements Design & advise on orchestration of data pipeline execution to ensure data products meet customer latency expectations, dependencies are managed, and datasets are as up-to-date as possible, with minimal disruption to end-customer use Ensure that designs are implemented with proper attention to data security, access management, and data cataloging requirements Approve pull requests related to production deployments Demonstrate solutions to business customers to ensure customer acceptance and solicit feedback to drive iterative improvements Assist in troubleshooting issues for datasets produced by the team (Tier 3 support), on an as-required basis Guide data modelers, business analysts and data scientists in the build of models optimized for KPI delivery, actionable feedback/writeback to operational systems and enhancing the predictability of machine learning models and experiments Qualifications Requires an extensive knowledge in designing a data model to solve a business problem, specifying a data pipeline design pattern to bring data into a data warehouse, optimizing data structures to achieve required performance, designing low-latency and/or event-driven patterns of data processing, creation of a common data model to support current and future business needs. This knowledge is considered to be normally acquired through the completion of a four-year University education in computer science, computer/software engineering or other relevant programs within data engineering, data analysis, artificial intelligence, or machine learning.

Experience guiding data lake ingestion and data modeling projects in a cloud environment (Azure & Databricks) Experience in modeling relational and in-memory models with star/snowflake schemas Experience with designing and implementing event-driven (pub/sub), near-real-time, or streaming data solutions, involving structured, semi-structured and unstructured data across various platforms and. A period of over 6 years and up to and including 8 years in data modeling, data warehouse design, and data solution architecture in a Big Data environment is considered necessary to gain this experience. "Please note, this is a real and current job vacancy.

Morson Edge does not use artificial intelligence to screen or select candidates."