RAVL helps technologists accelerate their careers. At RAVL, we connect strategy with execution, care deeply about the people we work with, and measure success by the lasting impact we leave behind. Our purpose is to build a team that puts real, sustainable business outcomes at the core of everything we do. We’re here to leave our clients better than we found them, and to create a place where our people are proud to Build. Better.As a Principal Data Engineering leader at RAVL, you will design, define, and elevate enterprise‑grade data and AI platforms that are secure, scalable, and high‑performance. Operating as a Community of Practice (COP) Leader within the BuildIQ organization, you will build horizontal data and AI capabilities that uplift all Organizations of Engagement (OOEs), providing expert architectural guidance, platform standards, and reusable accelerators across teams.You will thrive in environments of ambiguity, applying a delivery‑first, get‑shit‑done mentality to make progress visible and impactful. Success at RAVL means combining deep technical mastery in raw data engineering, data platform architecture, and applied AI systems with creativity, openness of mindset, and the ability to influence as a trusted outsider in complex client environments. This role is accountable not just for delivery, but for raising the performance bar of the entire data discipline.What does success look like in this role?Design and deliver enterprise data platforms, lakehouse architectures, and distributed raw data processing systems using contemporary cloud‑native technologiesArchitect and implement scalable batch and streaming pipelines, medallion architectures, data mesh patterns, and platform automation frameworks for resilience, governance, and securityStandardize and lead adoption of Databricks, Apache Spark, Delta Lake, and similar distributed data processing ecosystems across engagementsDefine and implement AI‑ready data foundations, including feature engineering pipelines, model‑ready data layers, and scalable experimentation environmentsBuild horizontal capabilities including ingestion frameworks, metadata and lineage standards, data quality and observability frameworks, secure‑by‑design platform blueprints,



and MLOps enablement patternsArchitect and guide implementation of MLOps workflows including model lifecycle management, model deployment strategies, monitoring, and governanceIntegrate with cloud‑native storage, data warehouses, APIs, ML platforms, vector databases, and enterprise systems while managing authentication, authorization, and secure data flowsApply secure coding practices, compliance standards, responsible AI principles, and automation‑first approaches across all data and AI platform designsDemonstrate a bias for action: ship reference architectures, reusable modules, AI accelerators, and templates that enable rapid, incremental deliveryMentor engineers, influence stakeholders, define governance standards, and shape technical and strategic direction across BuildIQSounds great, do my skills fit?Strong Grasp of Core Data & AI Engineering ConceptsDistributed data processing and Spark internalsLakehouse architecture and medallion design patternsData modeling for analytical, operational, and ML workloadsMetadata management, lineage, observability, and cost optimizationMLOps, feature stores, model versioning, and deployment strategiesAI system design fundamentals including LLM integration patterns and vector‑based retrievalCloud‑Native & Multi‑Cloud ArchitectureDeep experience designing and operating cloud‑native data and AI platforms on AWS, Azure, or GCPExperience working across multi‑cloud environmentsStrong understanding of networking, storage, identity, GPU workloads, and security boundaries in cloud data and AI systemsConsulting ExcellenceCollaboration, prioritization, and RAID ownership across multiple engagementsComfortable operating in ambiguity and creating clarity for teamsAbility to influence senior stakeholders as a trusted outsiderStrong facilitation, alignment, and decision‑making capabilityOperates as a high‑performing remote leader ensuring work is visible, transparent,



and uplifting to peersMindset Success Traits (Mandatory)Delivery‑first and outcome‑oriented (get shit‑done mentality)Creative and open to current approaches, including emergent AI technologiesComfortable working in ambiguity and creating clarityInfluential presence: able to shape direction across client and internal environmentsCurious, adaptable, emotionally aware, and committed to delivery excellenceNon‑Negotiable Technical SkillsCandidates must demonstrate proficiency in all of the following:Programming: Advanced Python and SQL, plus Scala or JavaData Platform Tooling: Databricks, Apache Spark, Delta LakeAI & ML Tooling: Experience with ML frameworks (e.G., MLflow, PyTorch, TensorFlow) and model lifecycle toolingInfrastructure & Automation: Terraform and CI/CD pipelinesCloud Platforms: Deep expertise in at least one of AWS, Azure, or GCP, with working knowledge of a secondSecurity & Governance: IAM, encryption (at rest and in transit), RBAC, secure coding practices, data governance, and responsible AI fundamentals(Candidates missing these will not be considered further.)Compensation & Hiring ProcessWe are recruiting for a future opportunity. The salary range for this role is $140 000 - $180 000 CAD, reflecting expected base pay. Total compensation may also include additional pay such as bonuses or incentives, depending on the position, and final offers are based on experience, skills, and qualifications. As part of our hiring process we may use technology, including AI‑based tools, to help summarize and assess applications; these tools assist our team and do not replace human review or decision‑making.Equal Opportunity & AccessibilityRAVL is an equal opportunity employer committed to building a diverse, inclusive, and accessible workplace. We welcome applications from all qualified individuals and provide accommodations throughout the hiring process upon request.We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.#J-18808-Ljbffr

📌 Principal Data Engineer - C$140,000 - C$180,000 A Year - Remote (Toronto)
🏢 RAVL
📍 Toronto