Senior Analytics Engineer

Data Modelling & Development Design and build domain, dimensional, and semantic data models using Snowflake and dbt. Develop scalable, reusable, and maintainable Data Products aligned with enterprise modelling standards. Build efficient incremental models and optimise complex transformations for performance and cost.

Understand end-to-end data lineage and work with source teams to resolve data gaps. Identify and remove duplicated, redundant, and deprecated models where appropriate. 2.

Data Quality & Engineering Standards Implement appropriate data quality, integrity, and testing controls across data models. Ensure models comply with established coding, naming, documentation, and testing standards. Participate actively in PR reviews and DCB , providing technical feedback to other engineers.

Investigate data quality issues, perform root-cause analysis, and implement sustainable fixes rather than downstream workarounds. Support implementation and adoption of Data Contracts for critical data elements. 3.

Automation & AI Build practical automation that improves development, testing, deployment, documentation, and monitoring. Develop solutions using Snowflake Cortex, LLMs, AI Agents, Python , and other relevant technologies. Contribute to reusable AI and automation capabilities rather than creating isolated solutions.

Identify repetitive engineering activities that can be automated to improve squad productivity. 4. Performance & Platform Optimi