About The Company
RAVL is a forward-thinking technology organization dedicated to delivering innovative data and AI solutions that transform businesses. Committed to excellence and inclusivity, RAVL fosters a collaborative environment where cutting-edge technologies and diverse talents come together to solve complex challenges. The company emphasizes continuous learning, strategic innovation, and responsible AI practices, positioning itself as a leader in the data engineering and artificial intelligence landscape. RAVL’s mission is to empower organizations with scalable, secure, and high-performance data platforms that drive actionable insights and sustainable growth.
About The Role
As a Principal Data Engineering Leader at RAVL, you will play a pivotal role in designing, defining, and elevating enterprise-grade data and AI platforms. Operating as a Community of Practice (COP) Leader within the BuildIQ organization, you will spearhead the development of horizontal data and AI capabilities that benefit all Organizations of Engagement (OOEs). Your responsibilities will include providing expert architectural guidance, establishing platform standards, and creating reusable accelerators to streamline team efforts. This role demands a delivery-first mindset, thriving in ambiguous environments while making impactful progress visible. Success in this position involves a blend of deep technical mastery in data engineering, platform architecture, and applied AI systems, combined with creativity, strategic influence, and a commitment to raising the performance standards of the entire data discipline.
Qualifications
- Strong grasp of core data and AI engineering concepts
- Expertise in distributed data processing and Spark internals
- Experience with lakehouse architecture and medallion design patterns
- Proficiency in data modeling for analytical, operational, and ML workloads
- Knowledge of metadata management, lineage, observability, and cost optimization
- Hands-on experience with MLOps, feature stores, model versioning, and deployment strategies
- Understanding of AI system design, including LLM integration patterns and vector-based retrieval
- Deep experience designing and operating cloud-native data and AI platforms on AWS, Azure, or GCP
- Experience working across multi-cloud environments
- Strong understanding of networking, storage, identity, GPU workloads, and security boundaries in cloud systems
- Proven consulting skills with the ability to collaborate, prioritize, and own risks across multiple engagements
- Ability to operate effectively in ambiguity, create clarity, and influence stakeholders as a trusted outsider
- Excellent facilitation, alignment, and decision-making skills
- Demonstrated leadership in remote work environments, ensuring transparency and team cohesion
- Proficiency in programming languages: Advanced Python, SQL, Scala or Java
- Experience with data platform tooling: Databricks, Apache Spark, Delta Lake
- Familiarity with AI & ML tooling: MLflow, PyTorch, TensorFlow, model lifecycle management
- Infrastructure automation skills: Terraform, CI/CD pipelines
- Deep expertise in at least one cloud platform (AWS, Azure, or GCP) and working knowledge of a second
- Knowledge of security and governance practices: IAM, encryption, RBAC, responsible AI principles
Responsibilities
- Design and deliver enterprise data platforms, lakehouse architectures, and distributed raw data processing systems using modern cloud-native technologies
- Architect and implement scalable batch and streaming pipelines, medallion architectures, data mesh patterns, and automation frameworks for resilience, governance, and security
- Standardize and promote adoption of distributed data processing ecosystems such as Databricks, Apache Spark, and Delta Lake across projects
- Define and implement AI-ready data foundations, including feature engineering pipelines, model-ready data layers, and scalable experimentation environments
- Build horizontal capabilities including ingestion frameworks, metadata and lineage standards, data quality and observability frameworks, secure platform blueprints, and MLOps patterns
- Guide and architect MLOps workflows encompassing model lifecycle management, deployment strategies, monitoring, and governance
- Integrate data platforms with cloud-native storage, data warehouses, APIs, ML platforms, vector databases, and enterprise systems, managing authentication and secure data flows
- Apply secure coding practices, compliance standards, responsible AI principles, and automation-first approaches in all platform designs
- Develop and ship reference architectures, reusable modules, AI accelerators, and templates to enable rapid, incremental delivery
- Mentor engineering teams, influence stakeholders, and shape governance standards and technical strategies across BuildIQ
Benefits
- Competitive salary range of $140,000 - $180,000 CAD, commensurate with experience and qualifications
- Comprehensive benefits package including health, dental, and vision coverage
- Opportunities for professional development and continuous learning in cutting-edge technologies
- Flexible work arrangements supporting remote work and work-life balance
- Collaborative and inclusive company culture fostering innovation and growth
- Participation in impactful projects that shape the future of data and AI solutions
Equal Opportunity
RAVL is an equal opportunity employer committed to fostering a diverse, inclusive, and accessible workplace. We welcome applications from individuals of all backgrounds and experiences. Accommodations are available throughout the hiring process upon request. We utilize AI tools to assist in the review and assessment of applications; however, all final decisions are made by our human recruitment team. We are dedicated to ensuring a fair and transparent hiring process
