Senior Data Engineer - Data Infra

This position is listed on behalf of a partner company, who manages all applications and next steps. Our partner is looking for a Senior Data Engineer - Data Infra based in Canada. This is a hands-on senior engineering role focused on building and scaling the data infrastructure that powers a rapidly growing technology organization. You’ll own critical ingestion pipelines, transformations, orchestration, data quality, and semantic-layer capabilities. Your work will turn complex, fragmented data sources into reliable and trusted data products used across business and technical teams. You’ll collaborate directly with stakeholders in Finance, Sales, Marketing, Manufacturing, and Machine Learning to translate needs into scalable solutions. The role also offers an opportunity to shape an AI- and agent-ready data platform, including governed access and data structures designed for emerging AI workflows. You’ll operate in a high-growth environment where ambiguity is common and hands-on technical ownership is highly valued. Accountabilities - Design, build, operate, and scale reliable data ingestion pipelines and connectors using technologies such as Fivetran, dbt, and BigQuery. - Develop and maintain data pipelines that bring information from diverse source systems into the central data warehouse. - Own and evolve core data-platform components, including dbt models, semantic layers, orchestration, data quality, and observability. - Build trusted, governed, and self-service data products that support business intelligence, analytics applications, and downstream teams. - Partner closely with Finance, Go-to-Market, Manufacturing, ML, and other stakeholders to understand requirements and translate them into effective data solutions. - Help establish data infrastructure that supports AI and agent-based workflows, including governed data access, LLM- and agent-compatible semantic layers, and appropriate scalability and safety controls.

- Contribute to the development and improvement of data engineering processes, standards, and practices in an evolving environment. - Troubleshoot data-platform issues hands-on, investigate root causes, and implement durable solutions. - Help drive alignment and informed decision-making around data architecture, tooling, and platform evolution. - Establish scalable approaches for operating data infrastructure as organizational needs and data volumes grow. Requirements - 5+ years of professional experience in data engineering, data platforms, analytics engineering, or another SQL-intensive data role; experience in high-growth startup environments is strongly preferred. - Proven experience building and operating production-grade ingestion pipelines, connectors, and transformation workflows using dbt or equivalent technologies. - Expert-level SQL skills and strong working proficiency in Python or a comparable programming language for automation and platform tooling. - Hands-on experience with Looker, Hex, dbt, or comparable BI and analytics technologies, with the ability to evaluate how these tools fit within a broader data platform. - Demonstrated ability to work cross-functionally, gather requirements, communicate technical concepts, and build consensus around data-platform decisions. - Experience establishing new data engineering processes and solutions in environments characterized by ambiguity and rapid change. - Strong troubleshooting, analytical, and problem-solving abilities, combined with intellectual curiosity and a willingness to work hands-on. - Strong communication and collaboration skills, with the ability to partner effectively with both technical and non-technical stakeholders. - Experience working with healthcare or other regulated, compliance-intensive environments is a plus. - Exposure to infrastructure supporting machine learning, AI, LLM-powered products, or agent-based workflows is an advantage.