SeniorSoftwareEngineer,DataSystems(Python)

## Accountabilities Design, build, and maintain scalable, high-performance data pipelines that ingest, transform, and normalize large-scale data from diverse external and internal sources. Develop and optimize APIs enabling secure, tenant-aware, and reliable integrations with third-party platforms and internal systems. Implement and support both event-driven and batch processing architectures to ensure data freshness, consistency, and scalability. Build robust ETL workflows handling complex data sources such as ad platforms, ecommerce systems, and real-time customer event streams. Design and maintain authentication and integration mechanisms including OAuth, API keys, and webhook-based systems. Implement observability, monitoring, and alerting systems to ensure transparency in data health, pipeline performance, and system reliability. Optimize data processing and infrastructure for cost efficiency, performance, and scalability in a cloud-native environment. Collaborate with cross-functional teams to evolve a flexible, extensible, and high-performing data integration platform. Ensure strong data integrity, governance, and maintainability across distributed and multi-tenant systems. Requirements 5+ years of experience in software engineering, data engineering, or integration engineering roles focused on data-intensive systems. Strong proficiency in Python for building scalable backend systems and data pipelines. Solid experience with ETL processes, API-based integrations, and orchestration of complex data workflows. Strong SQL expertise and familiarity with modern data warehouses such as BigQuery or equivalent systems. Hands-on experience with REST APIs, GraphQL, and webhook-based architectures. Experience implementing authentication systems such as OAuth 2.0 and API key-based access models. Familiarity with orchestration tools such as Airflow or similar workflow management platforms. Experience with containerization technologies such as Docker, with Kubernetes exposu