The Role
Work across the Customer family, particularly the Customer Decisioning domain
Sit between the domain architect (strategic high-level design) and data architects (detailed data structures) to design practical solutions
Analyse existing third-party solutions to propose viable internal alternatives aligned with Customer architecture principles
Design solutions that integrate customer, campaign, and marketing data systems
Propose suitable technologies (e.g. assessing when to introduce Kafka) to replace or improve current systems
Suggest and design necessary infrastructure components (primarily AWS & Snowflake, some Azure)
Your responsibilities:
Analyse current third-party marketing data solutions and design alternative internal solutions
Evaluate integration options including APIs, data schemas, file layouts, and table structures
Collaborate with the domain architect to ensure alignment with high-level business strategy
Work closely with data architects to understand detailed data structures and constraints
Propose infrastructure solutions primarily on AWS and Snowflake, with some Azure exposure as needed
Engage with multiple stakeholder groups to gather requirements and validate designs
Attend frequent stakeholder meetings, particularly in the early phases of onboarding
Produce solution designs and documentation for engineering teams to implement Leadership & Collaboration
Serve as a technical leader and mentor data engineers.
Partner with data scientists to deploy research models on Snowflake and AWS.
Engage with product and business stakeholders to align AI solutions with enterprise strategy.
Essential skills/knowledge/experience:
Strong experience with customer data and marketing data systems
Understanding of GDPR implications for customer data solutions
Knowledge of single customer view, master data management, CRM and Customer Data Platform concepts
Exposure to data quality tools, ETL processes and real-time paradigms.
Technical Skills:
API integrations and design
Experience with Snowflake and SaaS Marketing Platforms (desirable)
Ability to assess and recommend technologies such as Kafka
Familiarity with AWS infrastructure, with some exposure to Azure beneficial
Soft Skills:
Strong stakeholder management and communication skills
Ability to engage with diverse groups: marketing, product, finance, logistics, engineering, and architecture teams
Adaptability to quickly learn and evaluate new tools and technologies as needed
Stakeholders:
Direct: Domain Architect, Data Architects, Engineering Manager, Product Manager, Delivery Manager
Wider: Engineering teams, Marketing teams, Product stakeholders, Finance, Logistics, Media teams
Desirable skills/knowledge/experience:
Knowledge of data platforms (e.g. Snowflake, Azure Data Lake).
Understanding of monitoring, model performance tracking, and observability best practices.
Familiarity with orchestration tools like Airflow or Azure Data Factory.
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