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Added 14 mins ago
Project Manager, Sales Enablement & Executive Customer Engagement
Husky Technologies
Bolton, ON
Full-time
At Husky TechnologiesTM, our success is based on your success. Our ability to keep our customers in the lead is based on building the strongest team possible.
Added 16 mins ago
CIBC Toronto Pearson Airport Kiosk Opportunities
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Part-time
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Full-time
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Intermediate Project Controls/Scheduler - RMWB
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Full-time
We are looking for a highly organized and detail-oriented Project Controls Specialist/Scheduler to lead the planning and scheduling efforts for a major construction project. Reporting to…
Added 1 hour ago
Intermediate Specialist, Service Management
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Associate/Sr. Associate, Investments - Capital Partnerships
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Full-time
…both operating assets and a development pipeline of carbon capture and storage capacity, agricultural renewable natural gas and materials…
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Associate Vice President (AVP) - CAD P&C Accounting and Reconciliation Operations
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Project Manager, Capture and Optimization of Research Data (CORD) Platform
RI-MUHC | Research Institute of the MUHC | #rimuhc
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Contract
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Added 3 hours ago
Marketing Manager
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Added 5 hours ago
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emergiTEL

Data Engineer

Toronto, ON, Canada
Greater Toronto Area, Canada, Canada

Pay: $80 to $90 CAD / hour
Job type: Contract
Apply by: Oct 28, 2026
Posting language: English · French
Posted: Sep 28, 2026

Apply About employer

Applications open in a new tab.

Original job description

English section of this bilingual listing.

emergiTEL is hiring a Data Engineer for our client in the technology services industry. This role can be either contract or perm.

Location: Montreal, QC or Toronto, ON

Job Description (English)

Role Description

Design and deliver the data model, continuous data lineage framework, reconciliation approach, and audit trail infrastructure for governed data platform engagements at regulated financial institutions. Own the semantic and physical models that downstream reporting and reconciliation build against, design and build the lineage framework itself, and set the reconciliation and auditability standard the delivery team builds against.You Will

Design and document data models for confirmed sources and outputs, including source-to-target mappings, transformation requirements, and treatment approaches for data gaps identified during discovery.
Lead data model migration work, including mapping existing source structures to target models, defining transformation and enrichment logic, documenting migration approaches, and validating reconciliation to source systems.
Define the semantic model that the reporting layer builds upon in collaboration with data engineering stakeholders.
Design and build a continuous data lineage framework that captures, stores, refreshes, and presents lineage as a core platform capability.
Integrate lineage generation into the deployment lifecycle to ensure lineage is refreshed with every solution change.
Define and implement reconciliation approaches across source, transformed, and target datasets, including exception management.
Implement audit trail infrastructure capturing actor, timestamp, previous state, new state, and reason code for material data changes.
Author test specifications for data models, lineage, and reconciliation components and integrate automated data quality checks into deployment pipelines.
Apply enterprise data governance standards for sensitive data, privacy, and access controls as defined by the client.
Participate as an embedded member of an integrated delivery team, including standups, sprint planning, and stakeholder reviews.

Who You Are

Skilled in designing semantic and physical data models for governed data platforms.
Experienced building continuous data lineage frameworks rather than administering lineage products.
Proven background implementing reconciliation controls and audit traceability within regulated environments.
Deep expertise with AWS data platforms, including Aurora PostgreSQL, S3, Glue, Athena, Iceberg, Lambda, and orchestration services.
Committed to quality engineering through testing, validation, and automated quality controls.
Experienced in regulated financial services environments.
Able to communicate effectively with technical, business, and governance stakeholders.
Comfortable working as an embedded member of a client delivery team.

Description du poste (Français)

Description du rôle

This is an active position currently open for hiring. / Ce poste est activement ouvert au recrutement.Use of Artificial Intelligence / Utilisation de l'intelligence artificielle

Read the full bilingual original

emergiTEL is hiring a Data Engineer for our client in the technology services industry. This role can be either contract or perm.

Location: Montreal, QC or Toronto, ON

Job Description (English)

Role Description

Design and document data models for confirmed sources and outputs, including source-to-target mappings, transformation requirements, and treatment approaches for data gaps identified during discovery.
Lead data model migration work, including mapping existing source structures to target models, defining transformation and enrichment logic, documenting migration approaches, and validating reconciliation to source systems.
Define the semantic model that the reporting layer builds upon in collaboration with data engineering stakeholders.
Design and build a continuous data lineage framework that captures, stores, refreshes, and presents lineage as a core platform capability.
Integrate lineage generation into the deployment lifecycle to ensure lineage is refreshed with every solution change.
Define and implement reconciliation approaches across source, transformed, and target datasets, including exception management.
Implement audit trail infrastructure capturing actor, timestamp, previous state, new state, and reason code for material data changes.
Author test specifications for data models, lineage, and reconciliation components and integrate automated data quality checks into deployment pipelines.
Apply enterprise data governance standards for sensitive data, privacy, and access controls as defined by the client.
Participate as an embedded member of an integrated delivery team, including standups, sprint planning, and stakeholder reviews.

Who You Are

Experienced leading large-scale data migration engagements with proven reconciliation outcomes at go-live.
Skilled in designing semantic and physical data models for governed data platforms.
Experienced building continuous data lineage frameworks rather than administering lineage products.
Proven background implementing reconciliation controls and audit traceability within regulated environments.
Deep expertise with AWS data platforms, including Aurora PostgreSQL, S3, Glue, Athena, Iceberg, Lambda, and orchestration services.
Committed to quality engineering through testing, validation, and automated quality controls.
Experienced in regulated financial services environments.
Able to communicate effectively with technical, business, and governance stakeholders.
Comfortable working as an embedded member of a client delivery team.

Description du poste (Français)

Description du rôle

Concevoir et livrer le modèle de données, le cadre de lignage des données en continu, l’approche de rapprochement ainsi que l’infrastructure de piste d’audit pour des plateformes de données gouvernées au sein d’institutions financières réglementées. Assurer la responsabilité des modèles sémantiques et physiques utilisés par les couches de production de rapports et de rapprochement, concevoir le cadre de lignage et définir les normes d’auditabilité pour l’équipe de livraison.Responsabilités

Concevoir et documenter les modèles de données pour les sources et les sorties confirmées, y compris les mappings source-cible, les exigences de transformation et le traitement des écarts de données.
Diriger les travaux de migration des modèles de données en mappant les structures existantes vers les modèles cibles et en validant les résultats de rapprochement.
Définir le modèle sémantique utilisé par les solutions de production de rapports.
Concevoir et développer un cadre de lignage des données continu qui capture, stocke, met à jour et présente le lignage comme capacité essentielle.
Intégrer la génération du lignage au cycle de déploiement afin d’assurer une mise à jour à chaque changement.
Définir et mettre en œuvre l’approche de rapprochement entre les jeux de données sources, transformés et cibles.
Mettre en place une infrastructure de piste d’audit enregistrant l’acteur, l’horodatage, l’état précédent, le nouvel état et le code de justification.
Rédiger les spécifications de tests et intégrer des contrôles automatisés de qualité des données dans les pipelines de déploiement.
Appliquer les normes de gouvernance des données du client concernant les données sensibles, la confidentialité et la gestion des accès.
Participer activement aux cérémonies Agile et aux activités de livraison au sein de l’équipe intégrée du client.

Profil recherché

Expérience démontrée dans des projets de migration de données à grande échelle avec validation de rapprochement.
Expertise dans la conception de modèles de données sémantiques et physiques pour des plateformes gouvernées.
Expérience dans la création de cadres de lignage continus plutôt que dans l’administration d’outils de lignage.
Solide expérience en auditabilité et en contrôles de rapprochement dans des environnements réglementés.
Expertise approfondie des plateformes AWS incluant Aurora PostgreSQL, S3, Glue, Athena, Iceberg, Lambda et les outils d’orchestration.
Fort engagement envers la qualité logicielle, les tests automatisés et les contrôles de qualité des données.
Expérience dans le secteur des services financiers réglementés.
Capacité à communiquer avec des intervenants techniques, d’affaires et de gouvernance.
Aisance à travailler comme membre intégré d’une équipe client.

Vacancy Status / Statut du poste

This is an active position currently open for hiring. / Ce poste est activement ouvert au recrutement.Use of Artificial Intelligence / Utilisation de l'intelligence artificielle

emergiTEL uses artificial intelligence to help identify and source candidates for this role. All assessment and selection decisions are made by our recruiters, a human is always involved, and no applicant is evaluated or rejected by automated means alone. / emergiTEL a recours à l'intelligence artificielle pour aider à identifier et à trouver des candidats pour ce poste. Toutes les décisions relatives à l'évaluation et à la sélection sont prises par nos recruteurs ; une intervention humaine est systématiquement assurée, et aucun candidat n'est évalué ou rejeté uniquement par des moyens automatisés.

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More about this job

Responsibilities

Design and deliver governed data models, continuous lineage frameworks, reconciliation controls, and audit trail infrastructure for regulated financial institutions. Lead data migration and validation, define semantic models for reporting, and integrate automated testing and data quality checks into deployment pipelines.

Requirements

The role requires extensive experience leading large-scale data migrations and designing semantic and physical models, lineage frameworks, reconciliation controls, and auditability in regulated financial services. Candidates should have deep expertise in AWS data services, a strong commitment to automated testing and data quality, and the ability to work with technical, business, and governance stakeholders.

Skills

Data Modeling
Data Migration
Semantic Modeling
Physical Data Modeling
Data Lineage
Data Reconciliation
Audit Trail Infrastructure
AWS
Aurora PostgreSQL
Amazon S3
AWS Glue
Amazon Athena
Apache Iceberg
AWS Lambda
Data Quality Testing
Data Governance

Visa sponsorship

Not detected in the job text

Keywords

Data Engineering
Governed Data Platforms
Data Models
Source-To-Target Mapping
Data Transformation
Data Enrichment
Data Migration
Semantic Models
Physical Models
Continuous Data Lineage
Data Reconciliation
Exception Management
Auditability
Audit Trails
Automated Testing
Data Quality Controls
Deployment Pipelines
Data Governance
Privacy
Access Controls
AWS
Aurora PostgreSQL
Amazon S3
AWS Glue
Amazon Athena
Apache Iceberg
AWS Lambda
Orchestration Services
Regulated Financial Services
Agile Delivery

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