Senior Data Platform Engineer

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)

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