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Croesus

Data Governance and Quality Expert

Laval, QC, Canada

Job type: Full-time
Apply by: Oct 24, 2026
Experience: 5 to 8 years of experience in data management, governance, or quality.
Posting language: English
Posted: Sep 24, 2026

Apply About employer

Applications open in a new tab.

Original job description

Company Description

Croesus provides innovative, high-performance, and secure wealth management solutions that include portfolio management systems, portfolio rebalancing tools, and application programming interfaces (APIs). These solutions empower wealth management professionals to improve their productivity, enhance their client relationships, make informed decisions, and maximize the management of their assets under management.

Croesus’s mission is to provide a superior experience to its clients, users, partners, and employees and to positively impact the community. With more than 200 employees in its Montréal, Toronto, and Geneva offices, Croesus has won several industry awards for being a high-quality solution provider and an outstanding employer.

Position

The Data Governance & Quality Expert is responsible for designing, implementing, and evolving the mechanisms ensuring data quality, data lineage, governance, security, and compliance within the Croesus data platform.

The expert defines the governance frameworks and concretely implements them within the Databricks ecosystem : Unity Catalog configuration, quality rules in Lakeflow Spark Declarative Pipelines (SDP), data observability, and catalog and metadata management.

In a context where the adoption of AI-assisted development tools significantly accelerates the velocity of code and technical artifact production, the expert plays a key role in supervising development processes. They contribute to developing and enforcing quality standards, conventions, and guardrails that ensure deliverables (whether produced manually or with AI assistance) respect the platform's reliability, maintainability, and compliance requirements.

The expert works closely with internal teams to ensure that the data published on the platform respects the established quality, governance, and compliance standard .

Main Responsibilities

Data Quality

Define and maintain data quality standards applicable to the platform's pipelines and datasets.
Implement validation rules directly within SDP pipelines (EXPECT constraints, schemas, alerts) and ingestion processes.
Design and maintain automated data quality monitoring mechanisms, including anomaly detection and key metric tracking.
Participate in the review and validation of published data models and datasets, ensuring compliance with the conventions of the canonical data model.

Governance, Catalog, and Metadata

Manage and evolve the data catalog within Unity Catalog, including tagging, descriptions, and classification of data assets.
Maintain and structure metadata associated with datasets, pipelines, and data models.
Establish and maintain data lineage mechanisms to trace the origin and transformations of data across the Medallion architecture layers (Bronze, Silver, Gold).
Ensure that published datasets comply with established documentation, nomenclature, and governance standards.

Quality in an AI-Assisted Development Context

Identify and assess quality risks specific to code and artifacts produced with AI assistance (uncontrolled code, increased volume, false confidence, accelerated technical debt).
Design and implement validation strategies adapted to these risks: targeted automated tests, regression detection mechanisms, and risk-focused reviews.
Contribute to the evolution of the platform's quality processes to ensure they remain effective in the face of increased development velocity.
Ensure that data produced and transformed by these artifacts maintain the expected level of quality and compliance, regardless of their production method.

Collaboration and Support

Collaborate with data engineering teams to integrate quality and governance controls into data pipelines.
Support teams in applying data governance, quality, and documentation best practices.
Participate in the evolution of platform conventions and standards in line with the needs of data consumers.

Requirements

The working language is French, all internal meetings (including interviews) at Croesus are conducted in French, so a strong proficiency in French is mandatory.

Academic Training And Experience

Bachelor's degree in Computer Science, Software Engineering, Computer Engineering, Information Management, or a related field.
5 to 8 years of experience in data management, governance, or quality.
Experience with Databricks or an equivalent Lakehouse platform.
Experience in implementing data governance and quality management practices.
Experience in a SaaS or multi-tenant environment (asset).

Technical Skills

Good understanding of Lakehouse architectures, the Medallion architecture (Bronze, Silver, Gold), and Delta Lake.
Practical experience with Unity Catalog or an equivalent data governance system (catalog, permissions, data lineage, tagging).
Ability to configure data pipelines and integrate quality controls into them.
Understanding of data modeling principles (3NF, Data Vault, SCD Type 2) and ability to validate model compliance.
Knowledge of data auditability, data lineage, and compliance principles.
The following skills are assets:Familiarity with software quality challenges in an AI-assisted development context (code review, automated tests, conventions)Experience with data monitoring and observability tools (Grafana, alerts, metrics)Familiarity with data governance challenges in an AI/ML context (training data, feature stores, reproducibility)Experience with infrastructure as code (OpenTofu/Terraform) in a data platform context

Personal Skills

Comfortable both in defining frameworks and in concrete technical implementation.
Possessing a solution-oriented approach and the ability to identify risks while proposing concrete ways to address them.
Strong rigor and concern for the quality of data and technical deliverables.
Openness and aptitude for integrating artificial intelligence tools into work processes (validation, documentation, review, automation).
Ability to structure governance processes in complex and rapidly evolving technical environments.
Excellent analytical and problem-solving skills.
Ability to explain governance and compliance issues to various audiences.
Autonomy and sense of responsibility.

Why join Croesus ?

À la carte vacations
Annual salary + Corporate profit-sharing plan
Hybrid work, 2 days a week in office (Laval & Montreal offices)
Sports program
Gym available at our Laval head office
Telemedicine + group insurance (super useful for the family 😉 )
Group RRSP
Proximity to Montmorency & Mcgill metro
Ongoing training and development plan
Referral bonus
Indoor and outdoor parking & electric car recharging
Croesus boutique
Beautifully renovated and spacious office
Complimentary breakfast every morning
2X per month, Happy hours, prepared by our Croesus Life Partner

Are you interested in this challenge? Do you believe you have the qualities and expertise required for this position? Please complete your application today.

Although all applications are carefully analyzed, we will communicate only with those selected. Thank you for your interest in Croesus.

Are you interested in this challenge? Do you believe you have the qualities and expertise required for this position? Please complete your application today.

Although all applications are carefully analyzed, we will communicate only with those selected. Thank you for your interest in Croesus.

Apply About employer

More about this job

Responsibilities

Design and implement data governance, quality, lineage, catalog, metadata, and compliance controls across the Databricks data platform. Establish standards and validation processes for data pipelines and datasets, including safeguards for artifacts produced with AI-assisted development, and support engineering teams in applying these practices.

Requirements

Requires a bachelor's degree in a relevant field and 5 to 8 years of experience in data management, governance, or quality, with experience using Databricks or an equivalent Lakehouse platform. Candidates should understand Lakehouse and Medallion architectures, Unity Catalog or an equivalent governance system, data pipelines, data modeling, lineage, and compliance; strong French proficiency is mandatory.

Skills

Data Governance
Data Quality Management
Databricks
Unity Catalog
Lakeflow Spark Declarative Pipelines
Data Lineage
Metadata Management
Data Observability
Lakehouse Architecture
Delta Lake
Medallion Architecture
Data Modeling
Automated Testing
AI-Assisted Development
Infrastructure as Code
French Proficiency

Benefits

Flexible Vacation
Corporate Profit-Sharing Plan
Hybrid Work
Sports Program
On-Site Gym
Telemedicine
Group Insurance
Group RRSP
Ongoing Training and Development
Referral Bonus
Indoor and Outdoor Parking
Electric Vehicle Charging
Complimentary Breakfast
Employee Social Events

Visa sponsorship

Not detected in the job text

Keywords

Databricks
Unity Catalog
Lakeflow Spark Declarative Pipelines
Delta Lake
Lakehouse Architecture
Medallion Architecture
Bronze, Silver, and Gold Layers
Data Governance
Data Quality
Data Lineage
Data Catalog
Metadata Management
Data Observability
Data Classification
Data Pipelines
Data Ingestion
Data Modeling
Third Normal Form
Data Vault
Slowly Changing Dimension Type 2
Automated Testing
Regression Detection
AI-Assisted Development
Grafana
Infrastructure as Code
OpenTofu
Terraform
SaaS
Multi-Tenant Environments
French

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