Data Engineer Director

Overview

We are seeking an experienced Data Engineer to lead the development of a centralized Communications database. This role will be instrumental in aggregating, modeling, and visualizing data from both internal and external communications channels, including third-party agencies and tools. The successful candidate will partner with technology teams and external agencies to design robust data models, build scalable data pipelines, and deliver actionable insights through advanced BI and AI-driven visualizations. This role supports communications teams across the firm, including CCB Communications, US regional Communications, CIB Communications, Firmwide Impact and more.

Key Responsibilities

• Database Architecture & Data Modeling: Design and implement relational data models to support the aggregation and analysis of communications data from diverse sources (internal channels, external agencies, third-party tools).
• Data Integration & Pipeline Development: Build and optimize data pipelines for ingesting, transforming, and centralizing communications data, ensuring data quality and consistency.
• BI & Visualization Solutions: Develop and manage advanced BI solutions (e.g., Tableau, ThoughtSpot) to visualize the impact and outcomes of communications efforts, enabling data-driven decision-making.
• AI & Advanced Analytics: Collaborate with data scientists and analytics teams to deploy machine learning models and AI solutions that measure and predict communications effectiveness.
• Cross-Functional Collaboration: Work closely with communications teams across CCB, Corporate, CIB, Corporate Impact, and Employee Experience, as well as external agencies and technology partners, to understand data needs and deliver tailored solutions.
• Process Optimization: Identify and implement process improvements, automate manual workflows, and redesign infrastructure for scalability and performance.
• Documentation & Compliance: Document data models, metadata, and machine learning processes to ensure transparency, compliance, and knowledge sharing.

• Proven experience in data engineering, data modeling, and database architecture.
• Hands-on expertise in BI platforms and tools (e.g., Tableau, ThoughtSpot) for advanced analytics and data visualization.
• Proficiency in Alteryx, SQL, and Python for data integration, transformation, and analysis.
• Experience with cloud platforms (Databricks, AWS, Azure) and deploying/managing machine learning models in production.
• Strong understanding of MLOps and building automated pipelines for model deployment and monitoring.
• Demonstrated ability to collect, refine, and transform data from diverse sources, including third-party tools and external agencies.
• Excellent analytical, problem-solving, and communication skills.
• Experience working with cross-functional teams in a dynamic, fast-paced environment.
• Mastery of SQL, including designing and optimizing complex queries and database structures.