Domain Data Architect

Company Overview:

Bridgenext is a digital consulting services leader that helps clients innovate with intention and realize their digital aspirations by creating digital products, experiences, and solutions around what real people need. Our global consulting and delivery teams facilitate highly strategic digital initiatives through digital product engineering, automation, data engineering, and infrastructure modernization services, while elevating brands through digital experience, creative content, and customer data analytics services.

Don't just work, thrive. At Bridgenext, you have an opportunity to make a real difference - driving tangible business value for clients, while simultaneously propelling your own career growth. Our flexible and inclusive work culture provides you with the autonomy, resources, and opportunities to succeed.

Position Description:

Bridgenext is seeking a Domain Data Architect with demonstrated experience in financial services, asset management, or capital markets data domains. The role requires deep expertise in designing canonical data models for complex, multi-source environments, and the consulting posture to drive stakeholder alignment across business and technology teams.

The Domain Data Architect will lead the design of foundational data products for enterprise clients. You will own the architectural vision, engage stakeholders, and guide delivery teams through build and adoption. You will not write pipelines; you will set the design direction and make the architectural decisions that determine whether the product succeeds.

Key Responsibilities:

Lead discovery across business and technology stakeholder groups to understand current data landscape, identify pain points, and reconcile competing views of key data domains

Design canonical domain models, defining core entities, relationships, facts, dimensions, and appropriate grain for the business domain

Handle domain-specific variations across product types or asset classes through a flexible yet consistent attribute model

Design for multiple external data feeds in varying formats, without assuming control over upstream data sources

Define how mastered reference data flows into consolidated data products, including survivorship and matching logic for identifier conflicts across multiple upstream sources

Handle edge cases such as entities appearing in only one source, records without standard identifiers, and cross-domain or multi-currency scenarios

Define MVP scope - what is in, what is explicitly out, and why - balancing rapid time-to-value with long-term product vision

Treat deliverables as data products with consumer contracts, SLAs, quality baselines, versioning, and breaking-change policies

Identify top risks and design mitigations around data reconciliation, stakeholder alignment, and upstream data quality

Ensure designs are reusable and extensible for adjacent data products and downstream AI initiatives

Must Have Skills:

8+ years of experience in data architecture, with at least 3 years focused on investment management, capital markets, or asset/wealth management domains

Deep fluency in investment data concepts: positions, holdings, lots, corporate actions, IBOR vs. ABOR, TWR vs. MWR, tax lots, and multi-currency accounting

Proven experience designing canonical or domain models for complex, multi-source data environments with competing upstream formats

Hands-on knowledge of modern data platforms - Databricks, Delta Lake, Unity Catalog, or equivalent lakehouse architectures with Bronze/Silver/Gold conventions

Experience working with external data providers and sub-advisors whose feed formats you cannot control

Strong consulting posture: ability to lead stakeholder workshops, navigate ambiguity, build consensus across business and IT, and handle pushback constructively

Excellent communication skills - able to translate schema decisions into business terms and business constraints into technical scope

Proven ability to scope MVPs under tight timelines while preserving long-term reusability and extensibility

Preferred Skills:

Experience with SCD Type 2 for security master data, semantic layers, and data mesh / data product thinking

Familiarity with fund administration, custodial reconciliation, and sub-advisor reporting workflows

Exposure to multi-strategy asset managers spanning public equity, fixed income, alternatives, and hedge fund positions

Familiarity with Power BI, Excel-based business consumers, and designing data products for non-technical downstream users

Working experience with investment/trading core systems such as Aladdin, SimCorp Dimension, Bloomberg AIM, Eagle, Charles River, or Calypso

GenAI experience is an asset, including use of AI to accelerate data profiling, model documentation, or impact analysis

Canadian citizens and those authorized to work in Canada are encouraged to apply

#LI-CG1

#LI-REMOTE