Data Governance and Quality Expert

Croesus; Montreal (administrative region); On-site; CAD 110,000 - 150,000; Full time

Job summary

Croesus is seeking a Data Governance & Quality Expert to design, implement, and evolve data governance, quality, and security within the Croesus data platform. You will configure Unity Catalog, implement quality rules in Lakeflow SDP, and supervise data observability and metadata management.

You will work with internal teams to ensure published data meets governance and compliance standards, aligning with the Medallion architecture and AI-assisted development practices.

Qualifications

• Bachelor's degree in Computer Science or related field.
• 5–8 years of experience in data management, governance, or quality.
• Experience with Databricks or Lakehouse platforms and data governance practices.
• Experience in SaaS or multi-tenant environments.

Responsibilities

• Define and maintain data quality standards for pipelines and datasets.
• Implement validation rules in SDP pipelines and ingestion processes.
• Develop automated data quality monitoring and anomaly detection.
• Review published data models for canonical data model compliance.
• Manage Unity Catalog metadata, tagging, and classifications.
• Establish data lineage across Bronze, Silver, and Gold layers.
• Identify quality risks in AI-assisted development and design validation strategies.
• Collaborate with data engineering to embed governance in pipelines.

Skills

Data governance

Data quality

Databricks

Lakehouse

Metadata management

Data catalog

Data lineage

Quality assurance

Education

Bachelor's degree in Computer Science

Tools

Unity Catalog

Lakeflow SDP

Delta Lake

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.

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.