Excellent technical skills in back-end infrastructure, particularly data engineering
Expertise in ingesting, modeling, and maintaining data to enhance internal data processing capabilities
Efficient and productive approaches to processing data at scale
Ability to bridge the gap between technical and non-technical team members, communicating technical concepts and data-driven strategies clearly
Proficiency in Python for building scalable, reliable ETL/ELT pipelines
Experience with designing robust data models (e.g., dimensional, Data Vault) supporting business intelligence and analytics
Skills in creating analytics-ready datasets with efficient query performance
Knowledge of developing database schemas and optimizing database performance for transactional and analytical workloads
Capability to establish and enforce data governance practices, including data quality standards and metadata management
Strong collaboration skills with engineering, product, data science teams, and stakeholders
Ability to prioritize work based on data-driven insights and outcome-based goals
Participation in technical discussions on product directions, data modeling, and architectural decisions
Responsibilities
Design and implement robust data models (dimensional, Data Vault, etc.) that support business intelligence and analytics requirements
Build scalable, reliable ETL/ELT pipelines using Python that process data from multiple sources
Create and maintain analytics-ready datasets with efficient query performance for reporting and business insights
Develop database schemas and optimize database performance for both transactional and analytical workloads
Establish and enforce data governance practices, including data quality standards and metadata management
Prioritise work based on data-driven insights and outcome-based goals in collaboration with stakeholders
Work closely with engineering teams across the business, ensuring the best technical solutions are adopted, and elevate development standards through knowledge sharing and best practices
Collaborate across engineering, product, and data scientist teams to translate business requirements into technical solutions and ensure data assets are organized and accessible
Actively participate in technical discussions about new product directions, data modelling, and architectural decisions, ensuring the technology platform remains extensible