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Remote Data Entry Coding Jobs in Edmonton, AB (NOW HIRING)

This is a permanent position that is completely remote! Our client is a global enterprise company ... Hands-on experience coding in Python is required * Experience working with Business Intelligence ...

This is a permanent position that is completely remote! Our client is a global enterprise company ... Hands-on experience coding in Python is required * Experience working with Business Intelligence ...

Junior Wildlife Biologist

Edmonton, AB ยท Remote

CA$28 - CA$32.50/hr

Support crew leads with data entry and portions of field summaries or technical reports. * Travel/Work Split: * Full-time remote with approximately 80% field / 20% office (reporting, data review ...

... Code); you can review and improve the work, not just manage it * Deep experience with Kafka and ... Comfort with distributed teams and experience managing offshore or remote team members * Ability to ...

Write production-ready, well-tested, self-documenting code, and debug systematically across the ... Collaborate across multiple time zones, ensuring remote teammates are included, unblocked, and ...

Remote Data Entry Coding information

What is the difference between Remote Data Entry Coding vs Remote Medical Coding?

AspectRemote Data Entry CodingRemote Medical Coding
Required CredentialsBasic data entry skills, sometimes certification in data managementMedical coding certification (e.g., CPC, CCS)
Work EnvironmentHome or office, computer-basedHome or office, computer-based, often in healthcare settings
Industry UsageVarious industries including healthcare, finance, retailPrimarily healthcare industry
Search & Comparison IntentFocus on data entry tasks, less specializedFocus on medical coding, healthcare documentation

Remote Data Entry Coding involves basic data entry tasks across various industries, requiring minimal certifications. Remote Medical Coding is specialized for healthcare, requiring medical coding certifications. While both roles are remote and computer-based, medical coding demands industry-specific knowledge and credentials, making it more specialized than general data entry coding.

What is remote data entry coding?

Remote data entry coding involves entering, updating, and managing data in digital systems from a location outside a traditional office environment. This job typically requires accurately inputting information, such as codes, numbers, or text, into databases or software platforms. Employees often work from home and may handle sensitive data, making attention to detail and confidentiality important. Common industries hiring for these roles include healthcare, finance, and e-commerce. Remote data entry coding jobs usually require basic computer skills, familiarity with relevant software, and reliable internet access.

What are the most common challenges faced in a remote data entry coding role and how can they be managed?

One of the main challenges in a remote data entry coding position is maintaining high accuracy and attention to detail while working independently. Distractions at home and repetitive tasks can sometimes lead to errors or decreased productivity. Setting up a dedicated, quiet workspace and following a structured daily routine can help minimize mistakes. Additionally, staying connected with team members via regular check-ins and using collaboration tools ensures data consistency and timely communication of any issues.

What are the key skills and qualifications needed to thrive as a remote data entry coding specialist?

To thrive as a Remote Data Entry Coding Specialist, you need strong attention to detail, fast and accurate typing skills, and a solid understanding of data management procedures, often supported by a high school diploma or equivalent. Familiarity with data entry software, spreadsheets (such as Microsoft Excel or Google Sheets), and sometimes basic coding or database management systems is typically required. Excellent organizational skills, self-motivation, and effective time management are crucial soft skills for remote work success. These competencies ensure error-free data processing, maintain data integrity, and support efficient workflow in a remote environment.
What are popular job titles related to Remote Data Entry Coding jobs in Edmonton, AB? For Remote Data Entry Coding jobs in Edmonton, AB, the most frequently searched job titles are:
What job categories do people searching Remote Data Entry Coding jobs in Edmonton, AB look for? The top searched job categories for Remote Data Entry Coding jobs in Edmonton, AB are:
Infographic showing various Remote Data Entry Coding job openings in Edmonton, AB as of July 2026, with employment types broken down into 6% Internship, 66% Full Time, 11% Part Time, and 17% Contract. Highlights an 100% Remote job distribution.

Data Engineer - Intermediate (REMOTE) JP975

P@thlion Staffing Careers

Edmonton, AB โ€ข Remote

Full-time

Posted 14 days ago


Job description

Project Name:

Digital Regulatory Assurance System

Scope:

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.

This position 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.

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.
  • Other duties as needed