Job Description

About The Role We are looking for a Lead Data Engineer to architect and guide the design and implementation of a global data handling and synchronization platform. In addition to being hands-on, you will provide technical leadership to a small team of data engineers and advise on master data management (MDM) best practices, ensuring compliance with global data residency and privacy requirements (e.g., GDPR). Requirements 8+ years of experience as a Data Engineer, including at least 2 years in a technical leadership or lead role. Pyspark optimization experience. Strong expertise in Microsoft Azure data stack (Azure SQL, Data Lake, Data Factory, PySpark) and distributed data architectures. Proven experience with Master Data Management (MDM) and cross-region data synchronization. Familiarity with data privacy, security, and compliance (GDPR, etc.). Proficiency in Python, SQL, and ETL tools. Strong leadership, problem-solving, and communication skills. Preferred Experience with MS-SQL, Cosmos DB, Databricks, and event-driven architectures. Knowledge of CI/CD and infrastructure-as-code (Azure DevOps, ARM/Bicep, Terraform). Key Responsibilities Lead the design and implementation of data pipelines for global and regional data synchronization (Azure SQL, Data Lake, Data Factory, PySpark, etc.). Define the data architecture and drive MDM strategies for consistent, high-quality data across regions. Develop and enforce standards for secure handling of PII and non-PII data, ensuring GDPR and other compliance. Guide and mentor data engineers, reviewing code and solutions to ensure best practices. Partner with software architects, DevOps, and business stakeholders to integrate data flows with application logic and deployment pipelines. Oversee monitoring, alerting, and documentation for data processes within the existing frameworks. Provide technical guidance on data partitioning, replication, schema evolution, and data governance.