Director, Data Engineering (AI Native)

Job Description

• This position is listed on behalf of a partner company, who manages all applications and next steps. Our partner is looking for a Director, Data Engineering (AI Native) based in Canada. This is a senior leadership opportunity to shape and scale a modern data engineering organization within a high-growth, remote-first technology environment. The role owns end-to-end data systems, from ingestion and transformation to analytics and consumption by both humans and AI/LLM systems. You will lead multiple engineering teams through managers, defining the technical vision for data platforms, analytics engineering, and data governance. The position plays a critical role in enabling product, marketing, finance, and analytics teams with trusted, scalable, and self-serve data. It requires deep technical credibility combined with strong business acumen to influence decisions at the executive level. You will also drive AI-native practices across the data stack to improve speed, quality, and scalability of insights. This is a highly strategic role where leadership, architecture, and cross-functional impact converge.
• Accountabilities Define and own the end-to-end technical strategy for data engineering, including ingestion, transformation, modeling, orchestration, and serving layers across the organization. Lead and scale multiple engineering teams through managers, ensuring strong execution, talent development, and alignment with organizational priorities. Oversee analytics engineering practices, including data modeling standards, dbt architecture, testing frameworks, CI/CD workflows, and semantic layer design. Manage and optimize modern data platforms such as Databricks or equivalent lakehouse ecosystems, ensuring reliability, performance, and cost efficiency at scale. Partner with cross-functional leaders in Product, Engineering, Finance, and Marketing to translate business needs into scalable data solutions and roadmaps. Establish strong data governance, quality, documentation, and observability standards to enable trusted self-serve analytics across the organization. Drive AI-native transformation of the data function by integrating AI tools into workflows, pipeline optimization, and data quality processes. Own workforce planning, vendor strategy, and budget allocation for data infrastructure and engineering investments. Requirements 8–10+ years of experience in data engineering, analytics engineering, or data platform roles within high-scale technology environments. 5+ years of people management experience, including at least 3+ years managing managers and leading multi-team organizations. Strong technical expertise in modern data stacks, including dbt, Databricks, Snowflake, BigQuery, or equivalent platforms. Deep understanding of ELT/ETL architecture, data modeling (dimensional and semantic layers), and large-scale data pipeline design. Proven ability to lead architectural decisions and evaluate tradeoffs across data systems, performance, scalability, and cost. Strong executive communication skills with the ability to translate complex technical concepts into clear business insights. Demonstrated experience influencing cross-functional stakeholders and driving alignment across competing priorities. AI-native mindset with hands-on experience using AI tools to improve engineering productivity and data workflows. Strong business acumen with understanding of product analytics, growth metrics, and monetization models. Experience managing distributed or remote-first engineering teams is highly valued. Benefits Competitive compensation package including base salary and equity Comprehensive medical, dental, vision, life, and disability coverage Retirement savings plans with employer contributions (RRSP/401k equivalent depending on location) Flexible remote-first work environment across Canada Generous PTO and company-wide paid time off days Learning and development budget for training, courses, and career growth Home office and equipment support for remote productivity Equity program enabling long-term participation in company success
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