team.blue
1001 - 5000 employees
☁️ SaaS
🛍️ eCommerce
SaaS • eCommerce • Technology
team. blue is a leading digital enabler for companies and entrepreneurs, serving over 3. 3 million customers across Europe. With a team of more than 2000 experts, they provide innovative digital services aimed at empowering businesses through technology. team. blue operates a variety of brands and focuses on delivering excellent customer experiences.
Analytics Engineer
🕒 2 days ago
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team.blue
1001 - 5000 employees
☁️ SaaS
🛍️ eCommerce
SaaS • eCommerce • Technology
team. blue is a leading digital enabler for companies and entrepreneurs, serving over 3. 3 million customers across Europe. With a team of more than 2000 experts, they provide innovative digital services aimed at empowering businesses through technology. team. blue operates a variety of brands and focuses on delivering excellent customer experiences.
📋 Description
• 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.
🎯 Requirements
• 5+ years of experience in analytics engineering, data engineering, or a closely related data role. • Strong, hands-on proficiency with dbt (dbt Core or dbt Cloud) — this is a core requirement. • Experience working on Databricks (or a comparable cloud data platform such as Snowflake or BigQuery). • Solid understanding of dimensional modelling, data vault, or similar data warehousing patterns. • SQL excellence: complex transformations, window functions, query optimisation. • Proven ability to work autonomously across multiple data domains simultaneously, figuring out unfamiliar data with limited documentation. • Strong analytical mindset: able to interrogate data critically, spot anomalies, and validate logic end-to-end. • Excellent communication skills — comfortable talking directly with business stakeholders to elicit requirements and explain data concepts. • Experience working across diverse data domains (e.g. marketing, product analytics, customer care, financial/subscription data).
🏖️ Benefits
• Remote work options • Flexible working hours • Professional development opportunities
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