Première détection par notre source: il y a 1 heure
Data Steward (6A97890)
@ Referment
Montréal, Québec
SIGNAUX
En bref
Referment is hiring a Data Steward for a capital-markets technology company's Montreal office. The role owns data governance for financial-data domains and shapes how that data is presented to AI, including semantic layers in Snowflake and prompt engineering. The work is full-time, on-site four days a week with one day of flexibility, and not remote.
Responsabilités :
- Define and document business data definitions and ownership
- Set and monitor data-quality rules, controls and KPIs
- Investigate data issues through to root cause
- Build and maintain Snowflake semantic layers for AI products
- Develop and refine prompts to improve AI answer accuracy
Résumé des exigences :
- Experience in data management, governance or stewardship
- Working knowledge of Snowflake or comparable cloud warehouse, and SQL
- Experience with securities, trading, risk or market data
- Ability to explain technical data concepts in business language
- Interest in prompt engineering or semantic modelling (asset)
Outils et compétences
Source et dates
Type de source non vérifié · apify-linkedin
- Date publiée par l’employeur
- Non fourni
- Première détection par notre source
- 2026-11-14
- Mise à jour du dossier source
- 2026-11-14
Ces dates décrivent le dossier source, pas une vérification en direct du recrutement. Consultez l’offre originale.
Détails du poste
| Niveau | Intermédiaire |
| Domaine | Données et analytique |
| Heures par semaine | 40 (estimé) |
| Milieu de travail | Bureau |
| Position | Surtout assis |
| Exigences physiques | physique faible · ordinateur élevé |
| Langues | English |
Résumé et détails rédigés par l’IA à partir de l’offre; l’offre de l’employeur fait foi.
Referment
| Champ | Valeur |
|---|---|
| Offres sur Jobsy | 5 |
Description
Referment is working with a capital-markets technology company whose platforms help financial institutions trade, manage risk and run their financing businesses on a shared, governed data foundation. The role sits where financial-market data meets AI: the team builds the data products and intelligence that clients rely on. It is hiring a Data Steward for its Montreal office.
The Role
This role has two connected halves. First, you'll own end-to-end stewardship for assigned financial-data domains: defining and documenting business definitions, setting and monitoring data-quality rules, controls and KPIs, investigating issues through to root cause, and assessing the downstream impact of proposed changes before they ship. You'll maintain ownership, lineage, usage guidance and known limitations, and act as the trusted point of contact for your domains.
Second, you'll shape how that data is presented to AI. You'll build and maintain semantic layers in Snowflake that give AI-driven products the structure, definitions, relationships and business context they need, apply prompt engineering to develop, test and refine prompts that improve the accuracy and consistency of AI-generated answers, and make sure AI outputs stay grounded in well-governed data. You'll also act as L2 support for data incidents within your domains, diagnosing whether the root cause lies in source data, transformation logic, business rules or semantic definitions.
What We're Looking For
#Referment
The Role
This role has two connected halves. First, you'll own end-to-end stewardship for assigned financial-data domains: defining and documenting business definitions, setting and monitoring data-quality rules, controls and KPIs, investigating issues through to root cause, and assessing the downstream impact of proposed changes before they ship. You'll maintain ownership, lineage, usage guidance and known limitations, and act as the trusted point of contact for your domains.
Second, you'll shape how that data is presented to AI. You'll build and maintain semantic layers in Snowflake that give AI-driven products the structure, definitions, relationships and business context they need, apply prompt engineering to develop, test and refine prompts that improve the accuracy and consistency of AI-generated answers, and make sure AI outputs stay grounded in well-governed data. You'll also act as L2 support for data incidents within your domains, diagnosing whether the root cause lies in source data, transformation logic, business rules or semantic definitions.
What We're Looking For
- Experience in data management, data governance or data stewardship, ideally in financial services or capital markets.
- Working knowledge of Snowflake or a comparable cloud data warehouse, and SQL.
- Experience with at least one of securities or instrument reference data, trading lifecycle data, risk or market data.
- The ability to translate technical data concepts into clear business language for engineers, stakeholders and clients.
- Interest or prior experience in prompt engineering, semantic modelling or enabling AI agents.
#Referment
Journal
Visible seulement par vous. Conservé sur cet appareil, et dans votre compte une fois connecté.