Data Engineer

As an experienced Data Engineer, your role will involve designing, implementing, and optimizing a global data handling and synchronization solution across multiple regions. You will work with cloud-based databases, data lakes, and distributed systems, ensuring compliance with data residency and privacy requirements such as GDPR. Key Responsibilities: - Design and implement data pipelines for global and regional data synchronization using Azure SQL, Data Lake, Data Factory, PySpark, etc. - Develop solutions for secure handling of PII and non-PII data, ensuring compliance with GDPR and other regulations. - Build and optimize ETL processes for anonymization, transformation, global synchronization, and distribution of data. - Collaborate with software architects and DevOps to integrate data flows with application logic and deployment pipelines. - Set up monitoring, alerting, and documentation for data processes within the existing frameworks. - Advise on best practices for data partitioning, replication, and schema evolution. Qualifications Required: - 6+ years of experience as a Data Engineer in cloud environments, preferably Microsoft Azure. - Strong knowledge of Azure SQL, Data Lake, Data Factory, PySpark, and related services. - Experience in Spark Optimization. - Experience with distributed data architectures and data synchronization across regions. - Familiarity with data privacy, security, and compliance (GDPR, etc.). - Proficiency in Python, SQL, and ETL tools. - Excellent problem-solving and communication skills. - Hands-on and self-contributing. Preferred Qualifications: - Experience with MS-SQL, Cosmos DB, Databricks, and event-driven architectures. - Knowledge of CI/CD and infrastructure-as-code (Azure DevOps, ARM/Bicep, Terraform).,