Senior Data Engineer
13 ore fa
Firenze, Provincia di Firenze; Toscana, Italia
team.blue
Tempo pieno
Gratuito con email o Google
Salva questo lavoro e mantieni la tua ricerca organizzata
Crea un account gratuito per salvare lavori, creare avvisi e tornare a questa inserzione dalla tua dashboard.
Gratuito con email o Google
Overview As a Senior Data Engineer in Central Data Platform, you build and govern a scalable data ecosystem that delivers a 360-degree view of customers across 60+ brands. You will design high-value data products and data architectures that serve BI, operations, and AI initiatives. This is a cross-brand role, enabling trustworthy data as the single source of truth. You'll collaborate with Analytics, ML, and AI teams to drive measurable business value and transformative insights.
Responsabilità
Design and deliver scalable data products providing a unified source of truth across 60+ brands
Build and optimize ETL/ELT pipelines for large-scale structured and unstructured data
Lead secure, cost-efficient data architecture design and enforce best practices in modeling, orchestration, and observability
Implement data governance with lineage, metadata management, and quality controls for a reliable semantic layer
Collaborate with Analytics, ML, and AI teams to translate business needs into technical solutions
Tune data pipelines for peak performance focusing on indexing, query optimization, and schema evolution
Mentor junior engineers and foster a culture of technical excellence
Requisiti fondamentali
~7+ years in data engineering or data management
~ Advanced degree (Masters or PhD) in Computer Science, STEM, or related quantitative field
~ Proven track record deploying high-performance data solutions with measurable business value
~ Deep hands-on experience with Databricks (PySpark, Delta Lake, Unity Catalog) or equivalent table formats
~ Expert-level SQL with optimization and data modeling skills (Dimensional, Star Schema, Snowflake)
~ Proficiency in at least one cloud provider (AWS, Azure) and modern orchestration tools (Airflow, dbt)
~ Strong DevOps/Engineering skills (Docker, Kubernetes) and CI/CD with GitLab or GitHub
~ Experience with data versioning, schema evolution, and distributed metadata management
~ Strategic thinking
~ Effective communication with non-technical stakeholders
~ Problem-solving under fast-paced, multi-workstream environments
~ Databricks (PySpark, Delta Lake, Unity Catalog)
~ Advanced SQL and data modeling (Dimensional, Star Schema, Snowflake)
~ Cloud platforms (AWS, Azure)