First seen by our source: 3 hours ago
Data Steward (BAC42D7)
@ Referment
Montréal, Quebec
SIGNALS
Overview
Referment is hiring a full-time Data Steward for a capital-markets technology company's Montreal office. The role stewards financial-data domains (definitions, data-quality rules, lineage, incident root-cause work) and builds Snowflake semantic layers and prompts so AI-driven products stay grounded in governed data. The role is on-site, four days a week in the office.
Responsibilities:
- Own data definitions, quality rules and lineage for assigned financial domains
- Investigate data issues to root cause and act as L2 incident support
- Build and maintain Snowflake semantic layers for AI-driven products
- Develop and refine prompts to improve AI answer accuracy
- Assess downstream impact of proposed data changes
Requirements summary:
- Experience in data management, governance or stewardship, ideally in financial services
- Working knowledge of Snowflake or a comparable cloud warehouse, and SQL
- Experience with securities, trading lifecycle, risk or market data
- Ability to translate technical data concepts into business language
Tools & skills
Source and dates
Source type not verified · apify-linkedin
- Employer posting date
- Not provided
- First seen by our source
- 2026-11-14
- Source record updated
- 2026-11-14
These dates describe the source record, not a live verification that the employer is still hiring. Check the original posting.
Job details
| Seniority | Mid level |
| Department | Data & analytics |
| Hours per week | 40 (estimated) |
| Work setting | Office |
| Position | Mostly sitting |
| Physical demands | physical low · computer high |
| Languages | English |
Summary and details written by AI from the posting; the employer’s posting is the authority.
Referment
| Field | Value |
|---|---|
| Open jobs on Jobsy | 8 |
Job 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
Only you can see this. Kept on this device, and in your account when you sign in.