Description:
As an Analytics Engineer, you will focus on building and maintaining the analytical data layer that supports reporting, self-service analytics, and AI-enabled use cases. Working alongside Data Engineering and Analytics teams, you will help ensure data is reliable, scalable, and easy to consume.
Key responsibilities include:
- Building and maintaining analytical data models using dbt and SQL.
- Developing and optimising ELT/ETL processes to support analytics use cases.
- Collaborating with Data Engineering teams to prepare and model data for analytical consumption.
- Supporting and enhancing Looker environments, including LookML development.
- Implementing data quality checks, testing, monitoring, and documentation.
- Contributing to wider analytics projects that support business growth and product innovation.
- Identifying opportunities for automation and process improvement.
- Supporting the development of AI-enabled analytics capabilities and improving how contextual data is maintained for analytics tools and chatbots.
Your Skills & Experience
Essential requirements:
- Strong SQL skills with experience building production-grade data models.
- Hands-on experience with dbt.
- Experience designing and maintaining ELT/ETL pipelines.
- Strong experience with Looker and LookML.
- Understanding of data modelling best practices and analytics-focused data architecture.
- Experience working closely with both technical and non-technical stakeholders.
- Google Cloud Platform.
- Airflow, Cloud Composer, or equivalent orchestration tooling.
- Experience supporting AI, conversational analytics, or analytics chatbot solutions.
- Python for automation and data workflows.