Vice President, Data Engineering

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One of Canada’s Most Trusted Investment Brands.
At Picton Mahoney Asset Management (PICTON Investments), being alternative isn’t just what we do—it’s who we are.
Founded by industry pioneer David Picton, we’ve spent 20 years challenging conventional wisdom and redefining the investing landscape. As one of Canada’s most trusted investment brands, we are proudly independent—privately run, 100% employee-owned, and deeply committed to delivering results for our clients.
Thinking Alternatively is in Our DNA
With a team of 233 bold thinkers—one-third dedicated solely to investment management—we are specialists, not generalists. Managing over $19.9 billion (September 30, 2026) for institutional and retail clients, we navigate markets with conviction, resilience, and a forward-thinking approach.
We’re more than investors — we’re innovators. We challenge traditional investment mindsets, constantly pushing the boundaries to achieve our mission: To bring greater certainty to investors.
Our success is built on four guiding principles:
Treat investors’ money like our own.
Redefine the way investors invest.
Be human—always approachable.
Succeed together, one investment at a time.
These aren’t just words—they define how we think, how we invest, and how we work.
Now, we’re entering our next chapter. We’re transforming our brand and reshaping the way the world invests. If you think alternatively, embrace an entrepreneurial spirit, and thrive in a dynamic, bureaucracy-free environment, join us and be part of what’s next.
Thriving in Our Entrepreneurial Culture
At PICTON Investments, you’ll thrive in our creative and dynamic workplace, where collaboration and support are at the core of everything we do. At our firm, you’ll have the opportunity to take on significant responsibilities, work in a flexible environment, and tackle challenging projects from the outset. Our culture is designed for ambitious professionals who want to make an immediate impact while continuing to push boundaries and achieve our greater mission. You’ll be empowered with a high level of responsibility, trust, and flexibility, providing an exciting and creative space for you to help reshape how the world views alternative investments. With competitive total rewards, performance-based bonuses, and a clear path for career growth, you’ll have everything you need to develop both now and over the longer term.
The Opportunity
We are looking for a Vice President, Data Engineering to define and lead PICTON's data strategy across investment data, analytics, and AI, and to show what an AI-native data organization looks like in practice.
This is a strategic, hands-on leadership role. You will be accountable for data across all PICTON's businesses. You'll own the architecture, governance, and engineering capabilities that turn complex financial data into reliable, accessible and actionable products for people and for AI agents. We want someone who embraces AI in their processes and who can bring that way of working across an entire team.
You will work closely with Engineering, Investment, Product, and AI teams to build a modern data foundation that enables faster innovation and better decision-making.
What You'll Own
Data Strategy & AI-Ready Architecture
Serve as the single accountable owner for data across PICTON's businesses, setting direction, resolving competing priorities, and ensuring every business can rely on consistent, trusted data.
Define and execute PICTON's enterprise data strategy, architecture, and roadmap across Databricks, Snowflake, APIs, applications, analytics, and AI.
Own the technical build that enables PICTON's AI roadmap, working with AI and business leaders to sequence data capabilities so planned AI initiatives have the data, access, and governance they need to ship.
Design the platform so AI is a first-class consumer of data (e.g., well-governed semantic layers, rich metadata, and secure interfaces such as APIs and MCP servers that agents and LLM applications can reliably use).
Make pragmatic architecture decisions that balance performance, security, cost, and business needs, including the cost and governance of AI workloads.
Build a modern data platform supporting portfolio construction, performance, risk, analytics, and AI use cases.
AI-Accelerated Data Engineering & Governance
Lead the design of reliable, scalable pipelines for market, security, portfolio, and historical data, using AI coding assistants and agentic tools to shorten build and iteration cycles.
Apply AI to the data lifecycle itself, including automated data quality checks, anomaly detection, lineage and documentation generation, metadata enrichment, and reconciliation.
Establish practical standards for data quality, lineage, governance, security, and ownership, including guardrails for how AI tools and agents access sensitive financial data.
Evolve financial data models and semantic layers so data is consistent and reusable across products, teams, and AI systems.
Leadership, Mentorship & Culture
Build and lead a high-performing Data Engineering and Data Platform team.
Partner with Engineering, Investment, Product, and AI leaders to translate business needs into effective data solutions.
Identify opportunities to leverage modern data and AI technologies to create competitive advantage.
Communicate complex technical concepts effectively to both technical and business stakeholders.
What We're Looking For
10+ years of experience in data engineering, data platforms, architecture, or technology leadership, including significant team leadership experience.
Experience owning data across multiple business lines or functions, including balancing their competing needs and driving shared standards.
Experience building agentic AI solutions: designing agents and workflows that use tools, retrieve from enterprise data, and operate within clear security and governance boundaries, along with practical approaches to evaluating their accuracy and reliability.
Strong experience with modern cloud data platforms, particularly Databricks, Snowflake, SQL, APIs, and distributed data pipelines.
Deep understanding of financial and investment data, including securities, portfolios, market data, performance, risk, and time-series data.
Experience building data platforms that support analytics, applications, and AI/LLM workloads, including retrieval, semantic layers, and structured data access for models.
Strong understanding of data governance, quality, lineage, security, and ownership, and how these extend to AI systems.
Ability to move between strategic thinking and technical detail, making pragmatic architecture decisions.
Strong business acumen and exceptional communication and stakeholder-management skills.
Hands-on, current use of AI in your own workflow. You regularly use tools such as Claude Code, Cursor, GitHub Copilot, or similar to build, debug, document, and analyze, and you can give concrete examples of where it changed your speed or output.
Experience with LLM evaluation, observability, or AI cost management in production and familiarity with Model Context Protocol (MCP) or similar standards for connecting AI to enterprise systems.
A track record of mentoring engineers and shaping team culture. You can point to people you've developed and to teams that took on more ownership and improved how they work under your leadership.
Our Commitment to Employees
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Employment type
Full-Time

Work arrangement
No