• Design and implement scalable, cloud-native data pipelines for both batch and streaming use cases using tools such as Azure Data Factory, Databricks, Spark, and Kafka. • Build and maintain multi-dimensional data models optimized for performance, cost, and maintainability. • Integrate upstream data sources (ERP, CRM, external APIs) into core systems with strong attention to data integrity and lineage. • Optimize data flows for storage, processing, and performance using best practices within the Azure ecosystem. • Participate in a shared on-call rotation with Senior and Principal Engineers to ensure data platform reliability. • Resolve production issues, perform root cause analysis, and communicate effectively with stakeholders. • Support operational data tasks (e.g., schema changes, table updates) to maintain agility and consistency. • Contribute to process improvement and operational metrics that enhance system performance and team efficiency. • Partner with product managers, analysts, and engineers to deliver well-architected, scalable data solutions. • Provide peer mentorship and participate in code and design reviews to elevate technical standards. • Influence tooling, architecture, and design decisions that shape the long-term direction of the data platform. • Contribute to documentation, reusability practices, and knowledge sharing across teams.