Analytics Engineer

Overview

In this Analytics Engineer role within team.blue’s AI & Data function, you will transform raw data into analytics-ready datasets and data products that power reporting and insights across multiple brands. You’ll bridge the Data Management and Analytics teams, defining KPI logic, maintaining a semantic layer, and delivering reliable data assets at pace. You’ll work across diverse domains—marketing, product usage, customer care, revenue—and engage business partners to ensure data meaning and quality. This is a hands-on, autonomous role at scale in a Databricks-based environment with strong emphasis on governance and collaboration.

Responsabilità Design and build robust dbt models on Databricks to produce clean, conformed datasets

Define KPI logic with stakeholders to ensure consistent metrics across domains

Maintain and evolve the semantic/presentation layer with reliable, tested data products

Apply software engineering practices to analytics code, including version control, testing, CI/CD, and documentation

Onboard new data domains independently, exploring structure and modelling decisions

Engage domain owners to validate context and align on KPI definitions

Identify data quality issues early and coordinate with Data Management to resolve at the source

Bridge data engineers and analysts by translating analytical needs into engineering tasks and ensuring the presentation layer meets reporting needs

Contribute to data governance through naming conventions, lineage, and model cataloguing

Support extending analytics coverage to new brands and domains over time

Requisiti fondamentali 5+ years in analytics engineering, data engineering, or related data role

Strong, hands-on dbt (dbt Core or dbt Cloud) proficiency

Experience with Databricks or comparable cloud platforms (Snowflake, BigQuery)

Solid understanding of dimensional modelling or data warehousing patterns

SQL excellence with complex transformations and window functions

Ability to work autonomously across multiple data domains with limited documentation

Strong analytical mindset to interrogate data and validate logic end-to-end

Excellent communication skills with business stakeholders

Experience across diverse data domains (marketing, product analytics, customer care, financial/subscription data)

autonomy

curiosity

proactiveness

dbt (Core/Cloud)

Databricks or equivalent cloud platform

SQL