Analytics Engineer

• Design and build robust dbt models on Databricks that transform raw, ingested data into clean, conformed, and analytics-ready datasets.
• Define and implement KPI logic in collaboration with business and analytics stakeholders, ensuring consistent definitions across domains.
• Maintain and evolve the semantic/presentation layer, ensuring data products are reliable, tested, documented, and performant.
• Apply software engineering best practices to analytics code: version control, testing, CI/CD, and documentation.
• Independently onboard new data domains (e.g. marketing attribution, product usage, customer care, subscription data) with limited guidance — exploring the data, understanding its structure and meaning, and deciding how to best model it.
• Proactively engage business partners and domain owners to understand context, validate assumptions, and align on KPI definitions.
• Identify data quality issues early and work with the Data Management team to resolve them at source.
• Act as the connective tissue between data engineers and analysts: translating analytical needs into engineering tasks, and surfacing data realities back to the business.
• Work with the Analytics team to ensure the presentation layer meets reporting and self-service needs.
• Contribute to data governance: naming conventions, lineage documentation, and model cataloguing.
• Support the broader team in extending analytics coverage to new brands and domains over time.

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Analytics Engineer