Lead Data / AI Native Engineer

8+ years of Data Engineering and Software Engineering experience. 3+ years leading complex data engineering initiatives or engineering teams. Proven experience building enterprise-scale data platforms and pipelines. Experience delivering cloud-native analytics and AI solutions. Build highly available, secure, and scalable cloud-native data solutions. Develop ETL/ELT frameworks for ingesting, transforming, and publishing enterprise data. Implement high-volume distributed processing using Spark and PySpark. Leverage GitHub Copilot, Claude Code CLI, and AI-assisted development tools to accelerate engineering productivity. Technical Skills Build Proof of Concepts (POCs) and MVPs using AI-powered development approaches. Develop cloud-native solutions leveraging AWS and Databricks ecosystems. Build scalable architectures for data ingestion, processing, storage, and analytics. Key Expectations Strong experience in building enterprise-grade data pipelines, modern Lakehouse architectures, AI-enabled data products, and cloud-native platforms leveraging Databricks, AWS EMR, Spark, PySpark, and AI-native engineering tools such as GitHub Copilot and Claude Code. The role aligns with enterprise initiatives around AI-assisted engineering, intelligent automation, and AI-powered development workflows