Associate Data Scientist building predictive models and AI applications for AlgaeCal’s clinically - backed natural bone - loss solution. Transforming data into strategies that improve efficiency, sales, and profitability.
About the role
- Technical Lead owning pipelines, workflows, and data services for CapIntel’s wealth-management software platform. Leading data engineers while improving reliability, onboarding, observability, and financial-data capabilities.
Responsibilities
- Lead a team of data engineers day to day, deliberately matching people to work and planning capacity
- Grow ownership and technical leadership across the team
- Run performance management with clear expectations and timely actions
- Hire, onboard, and ramp new engineers
- Own the architecture and health of the Data platform, including serverless services, batch and streaming pipelines, legacy pipelines, search indexes, and durable workflow orchestration
- Drive evolution toward enterprise-grade data architecture, including data contracts, lineage, data quality checks, and DataOps practices
- Build proactive monitoring of data flows to identify quality issues before clients or advisors see them
- Formalize incident response, on-call expectations, runbooks, severity classification, incident communication, and blameless post-incident reviews
- Maintain quality through design reviews, code reviews, testing discipline, and a shared definition of done
- Own client data onboarding and implementation work for the Data team
- Partner with Product to translate client and advisor needs into data capabilities
- Contribute hands-on code, especially for new systems, high-risk changes, and reference implementations
- Measure and communicate team outcomes such as reliability, data quality, onboarding time, and delivery predictability
- Coach other teams on workflow, observability, and data patterns
- Use AI tooling in development, review, and internal knowledge workflows, and help define safe AI use on financial data
Requirements
- 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
- 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
- Strong SQL and experience with relational databases and search technologies, such as PostgreSQL and OpenSearch or Elasticsearch
- Track record of building observability into data systems, including structured logging, metrics, dashboards, and alerting
- Experience leading incident response and running post-incident reviews that lead to lasting fixes
- Evidence of delegation, ownership, and building a self-sufficient team
- Experience making engineering outcomes measurable and visible to non-technical stakeholders
- Composure under pressure
- Python experience is welcome as an addition
- Experience with financial instrument or market data and reconciliation challenges is a bonus
- Experience in a regulated industry and familiarity with data privacy obligations such as PIPEDA is a bonus
- Experience with DataOps practices, data contracts, data lineage, or data quality frameworks is a bonus
- Experience using AI-assisted development tools or building AI tools over internal data is a bonus
- Familiarity with Datadog or similar observability platforms is a bonus
Benefits
- Variable pay may be included depending on the role
- Equity may be included depending on the role
- Comprehensive benefits
- Flexible time off
- Dedicated opportunities for growth and development
- Perks and benefits designed to support growth and well-being
- Trust, respect, and collaboration-focused work environment
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