Senior Data Platform Engineer
team.blue · Firenze, Toscana ·
Overview As a Senior Data Platform Engineer, you will own and evolve a central data ecosystem to unlock strategic value from global assets. You'll build scalable data products that serve as the single source of truth for 60+ sub-brands, enabling BI, operations, and AI initiatives.
You'll shape secure, cost-efficient architectures and steer governance and observability. This role offers impact across a fast-growing multi-brand environment with a strong emphasis on collaboration and technical excellence.
Responsabilità Own and optimize the Data Infrastructure (Databricks, Airflow, dbt, Gitlab & AWS) for peak performance Design and deliver scalable data products providing a unified source of truth across 60+ brands Build and optimize robust ETL/ELT pipelines for large volumes of data with high availability and low latency Lead architectural design of secure, cost-efficient data architectures and enforce best practices in data modeling, orchestration, and observability Implement rigorous governance, lineage, metadata management, and quality controls for AI/ML readiness Act as strategic partner to Analytics, ML, and AI teams translating business needs into technical solutions Tune data platforms focusing on indexing, query optimization, and schema evolution Mentor junior engineers and promote technical excellence Requisiti fondamentali 7+ years of professional experience in data engineering or data management Experience with Databricks (PySpark, Delta Lake, Unity Catalog) Expert SQL skills and data modeling techniques (Dimensional, Star Schema, Snowflake) Proficiency with a major cloud provider (AWS, GCP, etc) and orchestration tools like Airflow or dbt Experience with multiple RDBMS (PostgreSQL, SQL Server, Oracle) Strong Docker/Kubernetes and CI/CD practices Experience with data versioning, schema evolution, and distributed metadata management Strategic thinking Clear communication of complex concepts to non-technical stakeholders Problem solving under fast-paced conditions Databricks (PySpark, Delta Lake, Unity Catalog) Advanced SQL and data modeling (Dimensional, Star Schema, Snowflake) Cloud proficiency (AWS, GCP)