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, we're focused on investors getting better service, understanding their investments, and feeling at ease knowing their future is secure.
Since launching in 2019, CapIntel has seen rapid adoption and industry recognition, earning top placements in Deloitte’s Technology Fast 50 Canada and Fast 500 North America in 2025, ranking us among the fastest-growing technology companies. To support this momentum, we're growing our team rapidly—investing in people who drive innovation at scale to expand our impact across the North American wealth management industry.
About the RoleAs Technical Lead for the Data team at CapIntel, you'll 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. You'll split your time roughly evenly between leading the team and building alongside it, and you'll 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. You'll work closely with the Data Product Manager, the other engineering team leads, Architecture, Client Solutions, and Implementation. You'll 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.
What You'll DoLead 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 team's 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
What We’re Looking For
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 Node.Js 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 Temporal.Io, 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 you've 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
Bonus Experience
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 team's workflow, or building AI tools over internal data
Familiarity with Datadog or similar observability platforms
This is an existing vacancy.
At CapIntel, we design compensation with intention. Each role is assessed against the impact, skills, and experience it requires, and we align our pay to competitive market data so candidates know what to expect from the start.
Your final offer will reflect your experience, skillset, and location. The listed range is a guideline, and the range for this role may be modified.
Compensation at CapIntel goes beyond base pay. Depending on the role, total rewards may include variable pay, equity, comprehensive benefits, flexible time off, and dedicated opportunities for growth and development.
If you’d like to understand more about our approach, we’re happy to walk through it during the hiring process.
$145,000 — $170,000 CAD
Notsureyou meet every requirement?We care most about mindset:yourdrive,curiosityandcommitmentto deliveringgreat work.While experiencematters, weknow thatcareersaren’talways linear. If this role excitesyouand you believe you can make an impactwith us,we want to hear from you.
Whyyou'llenjoy working hereLearn more aboutlife atCapIntelon our Careers page, including the virtues that inspire how we work and theperksand benefits designed to support your growth and well-being.We’rea 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 vision.If this speaks to you,we’dbe excited to have you with us.
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