Posted 2 days ago
Data Steward (CCDB26A)
@ Referment
Montréal, Quebec
SIGNALS
Overview
Referment is hiring a full-time Data Steward for its Montreal office, working with a capital-markets technology company whose platforms run on a governed data foundation. The role owns stewardship of financial-data domains and shapes how that data is presented to AI, including semantic layers in Snowflake and prompt engineering. The position is on-site, four days a week in the office.
Responsibilities:
- Define, document and monitor data-quality rules, controls and KPIs for assigned financial-data domains
- Investigate data issues to root cause and assess downstream impact of proposed changes
- Build and maintain Snowflake semantic layers for AI-driven data products
- Apply prompt engineering to improve accuracy and consistency of AI-generated answers
- Act as L2 support for data incidents within assigned domains
Requirements summary:
- Experience in data management, governance or stewardship, ideally in financial services
- Working knowledge of Snowflake or comparable cloud warehouse, and SQL
- Experience with securities reference, trading, risk or market data
- Ability to translate technical data concepts into business language
- Desirable: prompt engineering, semantic modelling or AI agent experience
Tools & skills
Source and dates
Source type not verified · apify-linkedin
- Employer posting date
- 2026-11-08
- First seen by our source
- 2026-11-10
- Source record updated
- 2026-11-10
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 | 1 |
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
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