RBC seeks a Lead Data Analyst to drive enterprise data platform initiatives, acting as a technical lead for data flow, AI/ML, and analytics.
Responsibilities
The Engineering team is driving multiple complex, enterprise-wide initiatives to build RBC’s next-generation data platform — one that is AI-ready, scalable, and trusted across the organization. In this senior role, you will serve as a technical lead and strategic partner: shaping how data flows, how AI/ML systems consume it, and how analytics insights reach decision-makers. You will own end-to-end delivery — from requirements through production — while mentoring teams and influencing platform direction. What will you do? Lead requirements definition and translate complex business needs into precise technical specifications: data contracts, transformation logic, AI/ML feature requirements, non-functional requirements, and acceptance criteria. Drive deep-dive analyses on customer behavior, product performance, campaign outcomes, and channel effectiveness — with a lens toward AI-augmented insight generation and predictive opportunity identification. Architect, build, and own dashboards, scorecards, and executive reporting frameworks; define standards for how data products are presented to senior leadership. Act as a technical bridge between business stakeholders, engineering, and data science teams — validating source-to-target mappings, enforcing data quality, and ensuring AI/ML pipelines consume reliable, well-governed data. Lead production readiness reviews, post-implementation validation, and continuous improvement cycles to ensure solutions are accurate, stable, and performing at scale. Mentor and guide junior analysts and engineers; establish best practices for analytics engineering, data quality, and AI-ready data design across the team.
Requirements
Must have: 10+ years of progressive experience as a data analyst, analytics engineer, or senior business systems analyst — with a track record of delivering at enterprise scale. Proven ability to lead complex, cross-functional data initiatives from ambiguous requirements through production delivery. Deep expertise in data mapping, acceptance criteria definition, UAT leadership, and production validation for analytics or data platform solutions. Expert-level SQL: complex multi-table joins, window functions, query optimization, and performance tuning on large enterprise datasets. Strong understanding of AI/ML workflows and how data platforms must be designed to support feature engineering, model training pipelines, and real-time inference. Hands-on knowledge of Kafka, schema registries, and event streaming concepts — including schema evolution, data contracts, and event quality validation. Deep familiarity with modern data platform architectures: data warehouses, Lakehouses (e.g., Delta Lake, Iceberg), and how they serve both BI and AI use cases. Exceptional stakeholder communication skills: able to translate technical complexity into clear narratives for senior and executive audiences. Nice-to-have: Domain experience in financial services — banking, credit data, or regulatory reporting. Familiarity with LLM/GenAI integration patterns: RAG pipelines, embedding workflows, or AI-assisted analytics. Experience with GitHub Actions and CI/CD for data pipelines. Knowledge of Debezium, GraphQL, or ELK Stack (Elasticsearch / Logstash / Kibana). Hands-on experience with cloud-native platforms: OpenShift, Kubernetes, S3 object storage. MongoDB experience: querying semi-structured data, aggregation pipelines for analytics use cases. Proficiency with BI tools (Tableau, Power BI) and data quality frameworks for trusted, governed reporting.
Benefits
A comprehensive Total Rewards Program including bonuses and flexible benefits, competitive compensation and pension plan. Leaders who support your development through coaching and managing opportunities. Work in a dynamic, collaborative, progressive and highly performing team. Opportunities to do challenging work, making a difference and lasting impact on communities. Enjoy a comfortable work environment with the option to dress casually. Network and build lasting relationships with developers from diverse backgrounds from across Canada and the world.
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