Job Description:

Enterprise Data Management & Data Quality Lead will lead the design and implementation of Asset Management's enterprise data quality operating model. This includes establishing data ownership across key investment data domains, partnering with business leaders and data stewards to define data quality standards, and implementing governance processes that ensure trusted, validated, and consumption-ready golden source data across the organization. The successful candidate will create the framework, ownership model, controls, and governance structure required to sustain enterprise-grade data quality at scale.

business.

Key Responsibilities

Enterprise Data Strategy & Governance

- Develop and execute the Asset Management Enterprise Data Management strategy.
- Define the target-state operating model for investment data governance and stewardship.
- Establish enterprise data standards, policies, control frameworks, and governance processes.
- Create the vision and roadmap for trusted "golden source" investment data across the organization.
- Lead prioritization of critical data initiatives and quality improvement programs.

Data Ownership & Stewardship Framework

- Establish enterprise data ownership and stewardship models across critical investment data domains.
- Identify and align business domain owners responsible for data quality, governance, and operational accountability.
- Lead workshops with business stakeholders to define domain-specific data quality requirements, critical data elements, validation rules, and acceptance criteria.
- Design governance processes that ensure ongoing ownership, monitoring, and continuous improvement of data quality controls.
- Create accountability frameworks for maintaining trusted golden source data across the enterprise.
- Ensure business validation rules are embedded within the data ecosystem and operationalized through automated controls and monitoring processes.
- Develop domain-level scorecards and data quality metrics to measure adherence to established standards.

Data Quality Framework Design

- Design and implement enterprise data quality standards and business validation frameworks.
- Define strategic controls across security master, reference data, pricing, benchmark data, positions, transactions,



and corporate actions.
- Establish critical data elements, data quality metrics, thresholds, KPIs, KRIs, and reporting standards.
- Create scalable exception management and remediation processes.
- Define data certification and sign-off processes for investment data consumers.

Leadership & Stakeholder Engagement

- Partner with senior business leaders to understand data consumption requirements and translate them into enterprise controls.
- Lead workshops with portfolio managers, traders, operations, risk, and compliance teams to capture and rationalize business validation rules.
- Act as the senior escalation point for critical data quality incidents.
- Influence organizational adoption of enterprise data governance practices.
- Provide leadership and mentorship to analysts, data stewards, and project team members.

Investment Data Domain Ownership

- Serve as SME for:
- Security Master
- Reference Data
- Pricing & Valuation Data
- Benchmarks & Index Data
- Positions & Holdings
- Transaction Data
- Corporate Actions
- Portfolio & Account Hierarchies
- Ensure business rules are embedded into enterprise platforms and workflows.
- Drive consistency across upstream and downstream data consumers

Technology & Platform Enablement

- Partner with engineering teams to operationalize data quality controls within Databricks and Azure environments.
- Guide architecture and integration decisions impacting investment data.
- Collaborate with teams supporting Bloomberg, BNY Eagle, FactSet, and other investment platforms.
- Promote automation and continuous monitoring of data quality controls.
- Define functional requirements for future-state EDM capabilities

Must Have Requirement:

- 10-15+ years of investment data management experience.
- Proven experience leading Enterprise Data Management initiatives within:
- Asset Management
- Wealth Management




- Pension Funds
- Institutional Investment Firms
- Major Financial Institutions
- Demonstrated experience building Security Master or Enterprise Data Management capabilities from the ground up
- Experience defining enterprise data governance frameworks and operating models.
- Strong understanding of investment workflows and downstream data consumption
- Ability to influence senior stakeholders and executive sponsors.
- Track record of creating enterprise standards and governance processes.
- Experience managing enterprise-wide data transformation programs

Expert experience with:

Databricks

Microsoft Azure

SQL and advanced data analysis

Bloomberg

BNY Eagle

FactSet

Data Governance Platforms

Data Quality Monitoring Solutions

- Demonstrated experience establishing Data Ownership and Data Stewardship frameworks within Asset Management, Wealth Management, or institutional investment environments.
- Proven track record of partnering with business domain owners to define critical data elements, data quality standards, and governance processes.
- Experience implementing operating models that produce trusted "golden copy" or "golden source" investment data for enterprise consumption.
- Experience creating accountability frameworks for data quality management across multiple business domains.

Nice to Have:

- Previous leadership experience at firms such as pension funds, asset managers, global banks, or institutional investment firms.
- Experience supporting cloud-based data modernization initiatives.
- Knowledge of data lineage, metadata management, and master data management solutions.
- Python, Spark, and advanced analytics experience.
- Exposure to both Asset Management and Wealth Management business models.

Soft Skills:

- Executive presence and stakeholder management.
- Strategic thinking coupled with hands-on delivery capability.
- Robust communication and influencing skills.
- Ability to translate technical concepts into business outcomes.
- Exceptional problem-solving and analytical skills.
- Ability to lead through ambiguity and drive organizational change.
- Collaborative and consultative leadership style.

Strong coaching and mentoring capability

📌 Data Management Team Lead - toronto
🏢 Swoon
📍 Toronto