Analytics Engineer
Pubblicato il 20-09-2026 - Team.Blue in Firenze
OverviewIn 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.
ResponsabilitàDesign 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 fondamentali5+ 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