Senior Analyst - Data & Analytics

Lead the design, build and maintenance of automated data pipelines and infrastructure across Google Cloud and Microsoft Azure platforms, enabling seamless data integration and stakeholder self-service in support of Canon's ITCG marketing, ecommerce and CRM team initiatives.

Data Integration & Development: Design, build and maintain collections of sophisticated data pipelines, models and visualisations that integrate marketing and sales data with other internal and external data sources, including automated collection from platform APIs such as Meta, LinkedIn and TikTok, in Google BigQuery and Power BI to support Canon's ITCG marketing, ecommerce and CRM team initiatives.

Exploratory Analysis & Insights: Perform exploratory and ad hoc analysis using Python/R and SQL to uncover trends, anomalies and business opportunities in ITCG digital marketing and sales data, and present insights and recommendations back to key stakeholders.

Self-Service Reporting: Create, present and maintain Power BI dashboards, datasets and ad hoc reports based on requirements gathered from key stakeholders, delivering actionable insights and supporting data-driven decisions.

Automation & Workflow Optimisation: Identify and automate repetitive data tasks, workflows and processes using Google Cloud and Microsoft Azure platforms, simplifying existing processes and bringing work currently done by agencies and vendors into automated, internally owned processes to improve efficiency and reduce manual data handling.

Data Architecture & Modelling: Develop and optimise data models that support scalable and efficient data storage, processing and retrieval within Google Cloud and Microsoft Azure platforms, building transformations in dbt or Dataform to engineering best practice, with code managed through Git version control, pull requests and CI/CD.

Data Quality & Validation: Implement data validation, cleansing, testing and alerting to ensure data is accurate and reliable before it's used in downstream systems; monitor pipelines, review code, resolve failed runs and data issues at the root cause, and collaborate with IT on any upstream changes required.

Semantic Layers & AI-Enabled Self-Service: Build and maintain the semantic layers that allow Conversational Analytics agents in Google Cloud to interpret data correctly, extending stakeholder self-service across the business.