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Data Assistant Jobs in Maple, ON (NOW HIRING)

25-053 Data Architect

Pickering, ON · On-site +1

$85 - $100/hr

... 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 ...

Sr. Data Specialist

Mississauga, ON · On-site +1

CA$99K - CA$132K/yr

This individual will provide in-depth advanced data product architecture and engineering and ... Note that McKesson does rely on a virtual assistant (Gia) for certain recruiting-related ...

Sr. Data Specialist

Mississauga, ON · On-site +1

CA$99K - CA$132K/yr

This individual will provide in-depth advanced data product architecture and engineering and ... Note that McKesson does rely on a virtual assistant (Gia) for certain recruiting-related ...

Data Infrastructure Engineer - Platform

Toronto, ON · On-site

CA$103K - CA$147K/yr

  • Medical

  • Dental

  • Retirement

  • PTO

These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed ...

You will manage and maintain the automated orchestration and ingestion of data using Fivetran and Airflow MWAA into our Redshift warehouse; assist our BI team by providing support and guidance for ...

These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed ...

Apply and follow best practices for automated regression testing to ensure the reliability and accuracy of data solutions * Assist in implementing change management and release management strategies ...

Data Scientist Rates: Up To $70.00 p/h INC. Structure: 12 month contract Location: North York, 1-2 ... At times, CorGTA or itsclient partners may utilize AI tools to assist with the hiring processes. By ...

Showing results 41-60

Data Assistant information

What is a data assistant?

Data Assistants are professionals who support data management processes within an organization. Their responsibilities typically include collecting, entering, cleaning, and maintaining data to ensure its accuracy and accessibility. They often work with spreadsheets, databases, and specialized software to organize and analyze information, making it easier for teams to make data-driven decisions. Data Assistants may also help prepare reports and collaborate with other departments to support research or business operations.

What are some common challenges data assistants face when managing large datasets, and how can they overcome them?

Data Assistants often encounter challenges such as data inconsistencies, missing information, and time-consuming data entry tasks when handling large datasets. To overcome these issues, it’s important to develop strong attention to detail, utilize data validation tools, and follow established data management protocols. Collaborating closely with data analysts and IT teams can also help identify and resolve data quality problems more efficiently, ensuring that the information remains accurate and reliable for stakeholders.

What is the difference between Data Assistant vs Data Analyst?

AspectData AssistantData Analyst
Required CredentialsHigh school diploma or equivalent; some roles may require basic certificationsBachelor's degree in data-related fields; certifications like Microsoft Excel or SQL are common
Work EnvironmentOffice settings, data entry centers, or remoteOffice environments, research firms, or corporate settings
Employer & Industry UsageAdministrative support in various industries, including healthcare, education, and retailData-driven decision making in finance, marketing, healthcare, and tech

While Data Assistants focus on data entry, organization, and basic support tasks, Data Analysts interpret data to provide insights and strategic recommendations. Both roles are essential but differ in complexity and scope.

What are the key skills and qualifications needed to thrive as a data assistant, and why are they important?

To excel as a Data Assistant, you need strong attention to detail, proficiency in data entry, and a basic understanding of data management principles, often supported by a high school diploma or equivalent. Familiarity with spreadsheet software such as Microsoft Excel, database platforms, and data visualization tools is typically required. Excellent organizational skills, reliability, and effective communication set top performers apart in this role. These abilities are vital for ensuring data accuracy, supporting efficient workflows, and facilitating informed decision-making within organizations.
What cities near Maple, ON are hiring for Data Assistant jobs? Cities near Maple, ON with the most Data Assistant job openings:

25-053 Data Architect

Morson Talent

Pickering, ON • On-site, Remote

$85 - $100/hr

Full-time

Re-posted 10 days ago


Job description

Job Description 25-053 Data Architect Resume Due Date: Monday, April 14, 2025 (5:00PM EST) Number of Vacancies: 1 Level: MP6 Hourly Rate: $85 - $100/hour Duration: 12 Months Hours of work: 35 Location: 889 Brock Road, Pickering (Hybrid - 4 days remote) Job Overview JOB FUNCTION As a Data Architect you will be responsible for leading the Azure architecture. design and delivery of data models 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 data lake & 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. JOB DUTIES Lead the architecture.

design and oversee implementation of modular and scalable data ELT/ETL pipelines and data infrastructure on Azure and Databricks 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 Bl 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 Develop Bicep or Terraform templates to manage Azure Infra as code Perform hands on data engineering work to build data ingestion and data transformation pipelines Qualifications EDUCATION 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 Experience guiding data lake ingestion and data modeling projects in the Azure cloud environment; 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.