Top Tech Jobs & Startup Jobs in Vancouver

Analyzes investment operations processes, identifies automation opportunities, translates business needs into requirements and future-state designs, and develops or coordinates solutions using Microsoft automation tools and Python. The role covers process mapping, testing, documentation, implementation, production support, governance, stakeholder collaboration, and user education while improving efficiency, controls, scalability, and operational risk management.

Business Analyst supporting investment operations and Information Systems. Partners with trading, portfolio management, compliance, vendors, and technology teams to define CRIMS requirements, configure workflows, document processes, support integrations and testing, and resolve production issues. The role requires knowledge of OEMS, trading lifecycles, portfolio management, compliance, and technical analysis, with SQL and C#.NET familiarity preferred.

Maintains and validates investment data across systems, manages scheduled data processes, delivers data quality signoffs, investigates exceptions, supports portfolio management requests, and improves workflows to increase efficiency, reduce risk, and strengthen data quality. Collaborates with investment teams, operational staff, engineers, and stakeholders on data management activities and projects.

Build and operationalize an investment constraints governance framework within Portfolio Compliance. Develop governance workflows, controls, process documentation, reporting, and automation solutions using Microsoft Power Platform, Power Automate, and Power BI. Partner with compliance, investment, legal, operations, and technology stakeholders to translate requirements into scalable processes, coordinate implementations and testing, improve efficiency, and support strategic operational risk initiatives.

Designs and manages scalable data integration pipelines, governance controls, semantic enrichment, and orchestration systems for enterprise AI and analytics. The role enables LLM, RAG, embedding, and multi-agent workflows; implements security, privacy, compliance, observability, auditability, guardrails, and monitoring for autonomous AI systems. Responsibilities include building connectors and APIs, detecting drift and hallucinations, documenting reusable integration patterns, and collaborating with AI engineers, governance teams, and business stakeholders.

Maintain and validate performance, attribution, and risk analytics across systems; investigate data-quality exceptions; manage scheduled analytics processes; improve automation, scalability, and governance; identify and mitigate process risks; implement controls; and serve as an analytics expert and escalation point. The role requires strong quantitative problem-solving, communication, independent judgment, and familiarity with Python, SQL, automation platforms, and modern data platforms.

Leads an Investment Insights team creating financial analytics that improve investment manager effectiveness. Responsibilities include designing and developing analytics, researching methodologies, partnering with investment teams and senior leadership, productionizing solutions, applying AI, resolving complex analytical issues, and managing analysts across Canada and India. The role also shapes team strategy, develops talent, manages risks, and builds stakeholder relationships.

Manage the end-to-end analytics production pipeline, including ingestion, calculations, distribution, dashboards, and semantic layers. Develop scalable investment analytics solutions across performance, attribution, risk, exposure, and investment models. Support proprietary and third-party analytics tools, resolve complex methodology issues, translate technical concepts for stakeholders, and improve workflows while managing process risks.

Analyze and improve enterprise data across Salesforce, Greenhouse, Dayforce, and related platforms. Responsibilities include data profiling, modeling, integration support, REST API testing, reconciliation, validation, quality analysis, documentation, and Agile release testing. The role partners with business, technology, engineering, and application teams to define requirements, transformation rules, mappings, and scalable data solutions that support reporting, analytics, and enterprise decision-making.

Owns the compute and storage infrastructure domain across on-premises and hybrid environments. Defines architecture, standards, guardrails, capacity, lifecycle, backup, recovery, and platform modernization strategies. Leads Kubernetes, virtualization, storage, GPU, AI/ML, and high-performance computing platform evolution while partnering with stakeholders, security teams, vendors, and platform owners. Provides hands-on technical leadership, guides complex delivery, manages platform health and costs, and evaluates emerging infrastructure technologies.