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Added 5 mins ago
Talent Acquisition Specialist
Clio
Canada
Full-time
Our Engineering and Product teams are expanding, and we are looking for a talented Technical Recruiter to join our growing Talent Acquisition team on a on a 12 month fixed term basis, with…
Added 5 mins ago
Talent Acquisition Specialist
Clio
Toronto, ON
Full-time
Our Engineering and Product teams are expanding, and we are looking for a talented Technical Recruiter to join our growing Talent Acquisition team on a on a 12 month fixed term basis, with…
Added 5 mins ago
Talent Acquisition Specialist
Clio
Vancouver, BC
Full-time
Our Engineering and Product teams are expanding, and we are looking for a talented Technical Recruiter to join our growing Talent Acquisition team on a on a 12 month fixed term basis, with…
Added 5 mins ago
Talent Acquisition Specialist
Clio
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Full-time
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Added 35 mins ago
Data and Analytics Specialist
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Mississauga, ON
Full-time
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Added 37 mins ago
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Chartwell

Data and Analytics Specialist

7070 Derrycrest Drive, Mississauga, ON, L5W 0G5, Canada

Job type: Full-time
Experience: Minimum 3–5 years of substantive hands-on experience designing, developing, debugging, and supporting enterprise data solutions using a modern cloud data stack.
Posting language: English
Posted: Sep 21, 2026

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Original job description

Job Overview / Purpose

We are seeking a highly skilled and hands-on Data and Analytics Specialist to join our growing Data and Analytics team. This role requires strong practical experience designing, developing, troubleshooting, and supporting enterprise data solutions using Snowflake, Azure Data Factory, Azure Data Lake, SQL, Python, and Power BI.

The successful candidate will be expected to become productive quickly within an established enterprise data environment. While business and domain knowledge will be provided through onboarding, the candidate should already possess the technical depth, troubleshooting capability, and independence required to work effectively with complex production data solutions.

This is a hands-on technical delivery role. The successful candidate must be comfortable investigating unfamiliar code and pipelines, tracing data and dependencies across multiple layers, identifying root causes, assessing downstream impacts, and implementing reliable production-ready solutions with limited technical hand-holding.

Key Accountabilities

Design, develop, optimize, and support robust ETL/ELT pipelines and enterprise data solutions using Azure Data Factory, Azure Data Lake, and Snowflake.
Independently investigate and troubleshoot complex production issues, tracing data across source systems, ADF pipelines, ADLS, Snowflake objects, transformations, business logic, and downstream reporting.
Write, read, modify, and debug advanced SQL, Snowflake views, stored procedures, streams, tasks, UDFs, and existing production code, including solutions developed by other team members.
Perform thorough root-cause analysis for pipeline failures, data discrepancies, performance issues, and unexpected system behaviour, including situations where the failure point is not immediately known.
Analyze existing data models, SQL logic, pipeline dependencies, transformations, and downstream consumers to determine end-to-end lineage and impact before implementing changes.
Develop and deploy scalable Python scripts and Azure Functions for automation, integrations, data processing, and advanced analytics use cases.
Develop and maintain Power BI reports, semantic models, datasets, measures, and transformations, including troubleshooting data and performance issues.
Translate business requirements into reliable and maintainable technical solutions while proactively identifying technical risks, dependencies, and data-quality concerns.
Support production data quality, reconciliation, governance, documentation, and metadata management practices.
Monitor and optimize production solutions for performance, reliability, scalability, automation, and maintainability.
Contribute to enterprise data models and technical standards while working effectively across both new development and established/legacy solutions.
Take ownership of assigned technical problems from initial investigation through resolution, validation, deployment, and post-production verification.

Qualifications

Education:

Undergraduate degree in Computer Science, Engineering, Mathematics, or related STEM field; a Master’s degree is an asset.

Experience:

Minimum 3–5 years of substantive hands-on experience designing, developing, debugging, and supporting enterprise data solutions using a modern cloud data stack.
Strong hands-on Snowflake experience, including practical use and troubleshooting of:
- SQL and complex transformations
- Views and stored procedures
- Streams and Tasks
- UDFs
- Query execution and performance troubleshooting
- Data lineage and dependency analysis
Strong practical experience with:
- Azure Data Factory
- Azure Data Lake Storage
- Azure Functions
- Advanced SQL development and debugging
- Python for data processing and automation
Demonstrated experience supporting production data pipelines and business-critical analytics solutions, including independently diagnosing failures and data discrepancies across multiple technology layers.
Experience working with existing enterprise codebases and unfamiliar data solutions, where investigation and back-tracing are required before changes can be made.
Snowflake certification (e.g., SnowPro Core or Advanced) is an asset; however, certification does not replace demonstrated hands-on technical proficiency.

Skills & Abilities:

Strong practical experience with Power BI, including semantic models, Power Query, DAX/measures, troubleshooting, and performance considerations.
Demonstrated ability to receive an unfamiliar data problem and independently trace the technical flow, isolate the root cause, determine downstream impact, recommend a solution, and implement the fix.
Strong ability to understand and troubleshoot SQL, Python, ADF pipelines, Snowflake stored procedures, data models, and existing business logic developed by others.
Strong analytical and problem-solving ability, particularly in situations where requirements are incomplete or the source of an issue is ambiguous.
Ability to work independently with limited technical supervision after initial business and environment onboarding.
Experience with DevOps, Git/GitHub, deployment practices, and source control is a strong asset.
Strong communication skills with the ability to clearly articulate technical findings, solution options, dependencies, and risks to technical and business stakeholders.
Strong ownership mindset with the ability to manage work from problem identification through production resolution while collaborating effectively within a fast-paced team.

Effort

Requires sustained mental focus for complex troubleshooting, root-cause analysis, data lineage investigation, coding, pipeline optimization, and report development.
Requires frequent hands-on use of cloud data platforms, development tools, query interfaces, logs, and monitoring systems for extended periods.
Requires the ability to move between new development, production support, debugging, and multiple stakeholder priorities.
High attention to detail is required when modifying existing production solutions, validating data, assessing downstream dependencies, and implementing technical changes.

Working Conditions

Work is primarily performed in a corporate office environment with the flexibility of a hybrid work model.
May involve occasional extended hours during production incidents, system deployments, data migrations, or critical project deadlines.
Requires regular collaboration with cross-functional business and technical teams.
Must be comfortable working in a fast-paced and evolving enterprise data environment where troubleshooting existing solutions is as important as developing new ones.

*Candidates should be prepared to demonstrate practical problem-solving and hands-on technical proficiency with Snowflake, SQL, and data pipeline troubleshooting as part of the interview process."

At Chartwell, we’re all about Making People’s Lives BETTER: the lives of our residents and their families, and the lives of our employees. Join an exceptional group of diverse, inspiring, and caring people who are empowered to provide personalized, human experiences for our residents and staff through the connections they make every day within our communities.

Chartwell’s commitment to diversity and inclusivity is a commitment to hiring people whose skills and abilities contribute the most to the success of the organization and who reflect the communities in which we live and work. We are an equal opportunity employer and welcome applications from a wide range of qualified candidates, including people with disabilities. If you have questions or require assistance with the application process, please email [email protected] or call 1-888-663-6448.

Chartwell may use artificial intelligence to assist in screening and assessing applicants for this position.

We thank all applicants for their interest, however, only those selected for further consideration will be contacted.

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More about this job

Responsibilities

The Data and Analytics Specialist will design, develop, and maintain robust ETL/ELT pipelines and enterprise data solutions using the Azure cloud stack and Snowflake. They are responsible for independently troubleshooting complex production issues, performing root-cause analysis, and ensuring data quality across all reporting layers.

Requirements

Candidates must possess 3–5 years of hands-on experience with modern cloud data stacks, specifically Snowflake, Azure Data Factory, and Python. A degree in a STEM field is required, along with strong analytical skills to manage and optimize complex production data environments.

Skills

Snowflake
Azure Data Factory
Azure Data Lake
SQL
Python
Power BI
ETL/ELT Pipelines
Data Modeling
Troubleshooting
Root-cause Analysis
Data Lineage
Azure Functions
Data Governance
Performance Optimization
DevOps
Git

Visa sponsorship

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Keywords

Snowflake
Azure Data Factory
Azure Data Lake
SQL
Python
Power BI
ETL
ELT
Azure Functions
Data Modeling
Data Lineage
DevOps
Git
GitHub
Data Governance
Cloud Data Stack
Performance Tuning
Stored Procedures
UDFs
Streams
Tasks
DAX
Power Query
Semantic Models
Root-cause Analysis
Production Support
Data Quality
Metadata Management
Automation
STEM

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