We are seeking a Data Engineer to architect and scale our next-generation big data ecosystem. Leverage Databricks to design robust ETL pipelines, implement sophisticated data models, and integrate diverse streaming and API sources. Bridge the gap between complex engineering requirements and actionable business insights, ensuring high-performing and compliant data infrastructure. Technical Functions Design and Orchestrate: Build and maintain high-performance, scalable ETL/ELT pipelines using Databricks to ensure seamless data flow. Systems Integration: Architect robust integrations across a diverse ecosystem, including internal/external APIs, relational databases, and real-time streaming sources. Data Refinement: Implement sophisticated transformation logic, data enrichment, and cleansing protocols to deliver "analytics-ready" datasets for downstream visualization. Optimization & Modeling: Develop high-efficiency data models and schemas, applying advanced indexing and partitioning techniques to maximize query performance and scalability. Ecosystem Management: Oversee and optimize cloud-based infrastructure, leveraging containerization and distributed computing to process massive datasets. Advanced Analytics Support: Utilize big data frameworks to empower Machine Learning (ML) initiatives and collaborate with Data Science teams to deploy predictive models and statistical algorithms. Automated Deployment: Design and implement "Zero-Touch" automation for CI/CD, encompassing build, test, and release processes to ensure rapid, reliable deployment. Integrity & Compliance: Execute rigorous data governance, lineage tracking, and access controls to ensure total compliance with global privacy regulations and internal quality standards. Documentation: Maintain comprehensive technical documentation for system configurations, data mapping, and architectural processes.