Technical Lead, Data

CapIntel is a software platform built for wealth management enterprises to help financial advisors explain complex investment strategies to their clients. Advisors at some of the biggest banks across North America are winning trust by using CapIntel to easily compare investments and create compelling educational presentations. Ultimately were focused on investors getting better service understanding their investments and feeling at ease knowing their future is secure.

Since launching in 2019CapIntelhas seen rapid adoption and industry recognition earning top placements in Deloittes Technology Fast 50 Canada and Fast 500 North America in 2025 ranking us among thefastest-growing technology companies. To support this momentumweregrowing our teamrapidlyinvestingin people who drive innovation at scale to expand our impact across the North American wealth management industry.

As Technical Lead for the Data team at CapIntel youll own the platform that every CapIntel product depends on: the pipelines workflows and services that ingest normalize and serve financial instrument data and client portfolio data to advisors and institutions. This is a hands-on leadership role. Youll split your time roughly evenly between leading the team and building alongside it and youll be accountable for both the reliability of the platform and the growth of the people who run it. The team has built a mature observable platform. Durable workflow orchestration standardized logging and metrics continuous monitoring and a quality-first definition of done are now in place and production incidents have become rare. Your job is to take that foundation to the next level: build a team that owns outcomes and can turn data reliability into a product advantage that advisors and investors actually feel. Youll work closely with the Data Product Manager the other engineering team leads Architecture Client Solutions and Implementation. Youll also be a go-to resource for other teams adopting the workflow and observability patterns the Data team pioneered. This role is ideal for a senior data engineer who has already led a small team prefers building leverage over being the hero and gets energy from raising the bar for everyone around them.

Lead the team

• Lead a team of data engineers day to day matching people to work deliberately and planning capacity ahead of need rather than in reaction to it
• Grow ownership and technical leadership across the team so delivery client onboarding and production support do not depend on any single person including you
• Run performance management with clear expectations and timely actions
• Hire onboard and ramp new engineers so they are independent quickly and handle transitions and handovers without disruption to clients

Own the platform

• Own the architecture and health of the Data platform: serverless services batch and streaming pipelines legacy pipelines search indexes and durable workflow orchestration
• Drive the evolution toward an enterprise-grade data architecture covering data contracts lineage data quality checks and DataOps practices
• Build systematic proactive monitoring of data flows so data quality issues are caught before a client or advisor sees them
• Formalise and embed incident response for the team: on-call expectations runbooks severity classification communication during incidents and blameless post-incident reviews that actually change the system
• Keep the quality bar high through design review code review testing discipline and a definition of done the whole team holds each other to

Deliver for clients

• Own client data onboarding and implementation work for the Data team making it faster and more predictable for clients and other teams.
• Partner with Product to translate client and advisor needs into data capabilities that create visible positive moments for users not just a platform that stays up
• Contribute hands-on code to the platform particularly on new systems high-risk changes and areas that need a reference implementation

Multiply beyond the team

• Measure and communicate the teams outcomes (reliability data quality onboarding time delivery predictability) so leadership other teams and clients can see the impact
• Coach other teams on the workflow observability and data patterns the Data team owns and contribute standards that other teams adopt because they work
• Use AI tooling as a core part of how the team works from development and review agents to internal knowledge tools and help define how the team uses AI safely on financial data

• 7 years of professional software engineering experience with at least 4 years focused on data engineering data platforms or ETL in production
• 2 years leading engineers as a team lead or tech lead including hiring performance management and growing others into technical leadership
• Deep current and TypeScript experience. This is a core requirement for the role; Python experience is a welcome addition alongside it
• Deep experience designing and operating data pipelines on AWS including serverless architectures
• Hands-on production experience with or a comparable durable workflow orchestration platform (for example Airflow Dagster or Step Functions) with a clear ability to ramp on Temporal quickly
• Strong SQL and experience with relational databases and search technologies (for example PostgreSQL and OpenSearch or Elasticsearch)
• A track record of building observability into data systems (structured logging metrics dashboards alerting) and using it to reduce incidents
• Experience leading incident response and running post-incident reviews that lead to lasting fixes
• Evidence that youve built a team that delivers without you: delegation ownership and a team that is better because you were there
• Experience making engineering outcomes measurable and visible to non-technical stakeholders
• Composure under pressure. You keep discussions constructive when systems clients or timelines are under stress

• Experience with financial instrument or market data and the reconciliation challenges that come with it
• Experience in a regulated industry and familiarity with data privacy obligations such as PIPEDA
• Experience with DataOps practices data contracts data lineage or data quality frameworks
• Experience using AI-assisted development tools as an established part of your own and your teams workflow or building AI tools over internal data
• Familiarity with Datadog or similar observability platforms

This is an existing vacancy.

We care most about mindset:yourdrivecuriosityandcommitmentto deliveringgreat experiencematters weknow thatcareersarentalways linear. If this role excitesyouand you believe you can make an impactwith uswe want to hear from you.

Learn more aboutlife atCapIntelon ourCareerspage including the virtues that inspire how we work and theperksand benefits designed to support your growth and team built on trust respect and collaboration. This powerseverything we doand creates a space to challenge and elevate each otheras we work towards our shared this speaks to youwedbe excited to have you with us.