Technical Lead, Data

Role overview Lead a data engineering team while continuing to build and operate the platform that supplies financial instrument and client portfolio data to downstream products. The role combines people leadership with hands-on ownership of pipelines, services, search, and workflow orchestration. The focus is on improving reliability and data quality, making client onboarding more predictable, and helping the team deliver without relying on individual specialists.

Responsibilities - Lead, hire, onboard, and coach data engineers; plan capacity, set expectations, and grow ownership across the team. - Own the architecture and health of serverless services, batch and streaming pipelines, search indexes, and durable workflows. - Improve data contracts, lineage, quality checks, and DataOps practices; monitor data flows to catch issues early. - Establish incident response practices, including on-call expectations, runbooks, severity levels, communication, and reviews that lead to lasting fixes. - Contribute code on new systems and high-risk changes, while maintaining strong design review, testing, and code quality practices. - Partner with product and client-facing teams on data onboarding and user needs; communicate outcomes such as reliability, data quality, and onboarding time.

Requirements - 7+ years of software engineering experience, including at least 4 years in production data engineering, data platforms, or ETL. - 2+ years leading engineers, including hiring, performance management, and developing technical leadership. - Deep, current experience with Node.js and TypeScript. - Experience designing and operating AWS data pipelines, including serverless systems. - Production experience with Temporal or a comparable durable workflow orchestration tool, and strong SQL skills. - Track record with observability, incident response, lasting operational improvements, and measurable outcomes for stakeholders.

Nice to have Experience with financial or market data, regulated environments or privacy obligations, data quality frameworks, AI-assisted engineering, or observability tools such as Datadog.

Benefits and work setup For eligible roles, total rewards may include variable pay, equity, comprehensive benefits, flexible time off, and professional development. The stated Ontario base salary range is CAD $145,000–$170,000; the final offer depends on experience, skills, and location.