Data Product Engineer

Description du poste (Français)

Description du rôle

emergiTEL is hiring a Data Product Engineer for our client in the technology services industry. This role can be either contract or perm.
Compensation: $72 - $90/hour OR Perm $120-$130k/annum
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

• 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.

Nice to Have

• Agentic lineage experience, including the use of LLM agents for lineage extraction, transformation analysis, and lineage maintenance.
• Broader agent-based system experience in data platform environments.
• DataOps expertise, including deployment pipelines, data contracts, expectations frameworks, and data quality tooling.
• Experience with graph databases such as Neo4j or Amazon Neptune and graph-based lineage exploration tools.
• Experience supporting Canadian banking data platforms operating under OSFI or similar regulatory requirements.
• Financial services reconciliation experience, including general ledger or revenue reconciliation.

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