Analytics Engineer
HybridLondon, England, United Kingdom
Job Summary
Build and maintain well-modelled data pipelines across Lyst's breadth of data and use cases, partnering with the customer experience tribe to model data behind features and show performance. Optimize the Snowflake warehouse for cost, complexity, and speed while migrating the BI stack from Looker to Omni. Develop semantic layers that enable stakeholders and AI tools to query data reliably, automate repetitive analysis, and enforce high data quality standards through testing and contracts. Review code, implement best practices, and support teams on data ingestion and modelling to bridge the gap between data creation and usage.
Required Qualifications
- Strong SQL, with experience working across large, complex datasets, spotting issues and keeping data quality high
- Experience with dbt and data modelling
- A good communicator, comfortable working with technical and non-technical stakeholders
- Sensible judgement about what to prioritise, so you can focus on the problems that matter most
- An eye for repetitive work that can be automated
- Comfortable using AI tools in your own workflow, and genuinely interested in how they are changing analytics engineering
- Experience with a BI tool such as Omni, Looker, Lightdash or equivalent
Desired Qualifications
- Experience with git, Terraform, Python or Jira
- Familiarity with cloud environments such as AWS, GCP or Azure
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