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About the Role

Design and build a modern, cloud-native, ML-ready data platform that supports transactional workloads, analytics, regulatory reporting, and the next generation of AI capabilities, including vector search and semantic retrieval. This role offers the opportunity to architect a platform from the ground up and shape the future of data and AI at a growing investment firm.

Responsibilities

• Design and evolve the shared data platform powering Hamilton ETFs' next-generation SaaS applications.
• Architect secure, scalable, and high-performing databases supporting advisor intelligence, CRM workflows, compliance monitoring, reporting, analytics, and future AI capabilities.
• Design and manage the core relational database architecture serving as the shared foundation for the platform's apps.
• Design scalable data models supporting advisor intelligence, CRM, marketing, compliance, reporting, and customer-facing applications.
• Own database performance, including indexing, partitioning, query optimization, replication, backups, recovery, and high availability.
• Establish robust data governance practices, including role-based access control, audit logging, encryption, data lineage, and retention policies aligned with Canadian regulatory requirements.
• Support secure ingestion, normalization, and deduplication of large financial-industry datasets, including the Canadian advisor database.
• Design structures supporting ML features such as lead scoring, intent detection, advisor similarity, anomaly detection, and natural-language reporting.
• Work with the Full Stack Developer to define API-ready patterns, stored procedures where appropriate, and efficient service-layer access.
• Ensure clean, governed data flows into HubSpot as the commercial source of truth.
• Help design future infrastructure: data warehouse, event streaming, vector database, semantic search, and analytics layers.
• Document standards, naming conventions, backup procedures, security controls, and data lifecycle policies.
• Undertake other work or special projects assigned for the overall benefit of Hamilton ETFs.

Requirements

• Strong understanding that the database is the foundation of the product, with passion for performance, security, clean data models, maintainability, and future flexibility.
• Comfort in an early-stage environment and energized by creating a strong foundation.
• Ability to work closely with application developers and product leadership.
• Strong documentation and operational discipline.
• Architectural mindset with the ability to design systems that will scale as products, data volumes, and AI capabilities evolve.
• Post secondary diploma in computer science, computer engineering or other relevant programs.
• 5+ years designing and supporting relational databases as a Database Engineer, Data Engineer, Database Developer, or similar role.
• Strong PostgreSQL experience: performance tuning, indexing strategies, schema design, and database security.
• Experience designing databases for SaaS, CRM, workflow, reporting, or financial services platforms.
• Strong grasp of data privacy, auditability, role-based access control, encryption, backup, and disaster recovery.
• Experience with ETL/ELT pipelines, data imports, deduplication, validation, and large structured datasets.
• Masters Degree an asset.
• PostgreSQL at scale: partitioning, replication, read replicas, materialized views, and query profiling.
• Experience with cloud platforms such as AWS, Azure, or GCP.
• Experience with data warehouse or analytics tooling.
• Experience with vector databases such as pgvector, Qdrant, Pinecone, Weaviate, or similar.
• Experience supporting ML workflows, semantic search, embeddings, or LLM-backed applications.
• Experience in financial services, wealth management, asset management, capital markets, or regulated environments.
• Familiarity with SOC 2, ISO 27001, audit controls, data retention, and compliance reporting.
• Familiarity with event-driven architectures, message queues, or streaming pipelines.
• Authorized to work in Canada.
• Not currently sponsoring any temporary or permanent work visas.

Skills

• PostgreSQL
• Performance Tuning
• Indexing Strategies
• Schema Design
• Database Security
• SaaS
• CRM
• Workflow
• Reporting
• Financial Services
• Data Privacy
• Auditability
• Role-Based Access Control
• Encryption
• Backup
• Disaster Recovery
• ETL/ELT
• Data Imports
• Deduplication
• Data Validation
• Large Structured Datasets
• Cloud Platforms (AWS, Azure, GCP)
• Data Warehouse
• Analytics Tooling
• Vector Databases (pgvector, Qdrant, Pinecone, Weaviate)
• ML Workflows
• Semantic Search
• Embeddings
• LLM-backed Applications
• SOC 2
• ISO 27001
• Audit Controls
• Data Retention
• Compliance Reporting
• Event-Driven Architectures
• Message Queues
• Streaming Pipelines

Location

• Toronto, ON

Work Type

• 100% onsite
• Full-Time Permanent

Experience Level

• 5+ years designing and supporting relational databases

Education Level

• Post secondary diploma in computer science, computer engineering or other relevant programs
• Masters Degree an asset

Salary/Compensations

• $110,000 - $125,000 plus incentive compensation

Benefits

• Competitive compensation package
• Comprehensive health and wellness benefits

About the Company

• Hamilton ETFs is building a SaaS platform—a suite of applications designed to power every aspect of our business, including sales, marketing, data intelligence, compliance, reporting, and AI-assisted workflows.
• Purpose-built for the unique needs of a Canadian asset manager, this platform will be the foundation for how we operate and innovate.
• Hamilton ETFs is one of Canada’s fastest growing exchange traded fund (“ETF”) providers.
• Based in Toronto’s financial district and with ~$17 billion in ETF assets under management, we are seeking a motivated individual to join our entrepreneurial team of experienced and talented professionals.

Equal Opportunity

• Hamilton ETFs is committed to meeting the accessibility needs of all applicants throughout the recruiting and selection process. Please let us know about any accommodation and/or support requirements.
• Some stages of our recruitment process may use AI-assisted tools to support recruitment efforts; however, all applications are screened and assessed by human reviewers. In addition, all final hiring decisions are made by humans.