Director of Data & Analytics Engineering

Role Overview

• Define and execute a clear data and analytics strategy aligned with Reach’s business goals and growth priorities.
• Partner with senior leadership in Risk, Capital Markets, Finance, Operations, Marketing, and Product to embed data into every key decision.
• Establish a unified architecture and measurement framework across business lines.
• Anticipate trends in data and AI, positioning Reach to adopt high-impact innovations ahead of the curve.
• Drive transformation toward a cloud-first, scalable, governed data platform that enables real-time analytics and responsible AI.
• Lead the evolution of Reach’s modern data stack (Fivetran, dbt, Snowflake, Tableau) to maximize reliability, scalability, and cost efficiency.
• Implement best practices for ingestion, transformation, observability, and data quality.
• Champion strong data governance, lineage, and discoverability through automation and tooling.
• Continuously evaluate new technologies and vendors that deliver measurable business value.
• Develop a unified analytics layer that powers self-service reporting and executive decision-making.
• Ensure business teams can independently access accurate, timely insights to drive product, risk, and operational outcomes.
• Translate complex data into clear narratives that inform strategy and create business clarity.
• Ensure data product ownership principles by ensuring models, pipelines, and datasets are treated as reliable, discoverable, and reusable assets.
• Partner with the Data Science team to evolve ML models for credit, fraud, pricing, and collections.
• Collaborate to expand AI/ML use cases into new domains such as marketing, service, and operations.
• Help establish a scalable, explainable ML Ops practice to ensure compliant and efficient model development and deployment.
• Define processes that allow for rapid experimentation and measurable impact.
• Establish clear SLAs, data quality standards, and cost controls to ensure the data function operates as a disciplined, high-performing organization.
• Embed data observability and incident management into daily workflows.
• Continuously improve internal processes to increase delivery velocity, reduce latency, and enhance reliability.
• Build, mentor, and scale a high-performing data team spanning engineering, analytics, and data product management.
• Foster a culture of accountability, curiosity, and innovation grounded in transparency and trust.
• Develop leadership depth within the team and support cross-functional collaboration across departments.
• Represent Reach’s data capabilities internally and externally as a thought leader and advocate.

Requirements

• 10+ years of experience in data and analytics, with at least 5 years leading high-performing cross-functional teams.
• Deep understanding of modern data architecture, governance, and analytics within a regulated industry (fintech, lending, or financial services).
• Proven track record of scaling data teams and platforms in high-growth environments.
• Strong communicator who can simplify complex data concepts for executives and non-technical stakeholders.
• Experienced in operationalizing data governance, self-service analytics, and data products.
• Strategic thinker who can balance long-term vision with hands-on execution.
• Forward-looking leader with curiosity about AI, automation, and emerging data technologies.

Tech Stack

• Cloud
• Tableau

Benefits

• Healthcare, Life Insurance, 401k/RRSP Match
• Paid Time Off, Parental Leave
• Disability (short-term, long-term), Employee Assistance Program