• Build Next-Gen AI-Based Analytics Platform • Design and develop an AI-native data insights and analytics platform that delivers real-time, intelligent insights to business stakeholders • Integrate AI agents, LangChain, LangGraph, and other AI frameworks as core platform capabilities, not afterthoughts • Build APIs and microservices that power analytics features and serve insights to end users • Create user-facing analytics capabilities that are intuitive, fast, and powered by AI • Architect Real-Time Data Infrastructure • Design and implement real-time data pipelines using streaming technologies (Kafka, AWS Kinesis, etc.) • Build event-driven architectures that process and analyze data as it arrives • Create high-performance data processing jobs optimized for speed and scalability • Ensure data flows are reliable, monitored, and self-healing • Software Engineering Excellence • Apply software engineering best practices: clean code, testing, CI/CD, version control, code reviews • Write production-grade Python and SQL code that is maintainable, testable, and well-documented • Design systems with scalability, observability, and reliability in mind • Build with modern development practices and tools • Innovation and Problem-Solving • Proactively identify inefficiencies, gaps, and opportunities for improvement in data systems and processes • Experiment with new technologies and approaches to solve complex data challenges • Drive innovation by proposing and implementing creative solutions • Take ownership of problems and see them through to resolution—be a self-starter who doesn't wait to be told what to do • Migration and Maintenance • Support and maintain existing data warehouse infrastructure during the transition period • Plan and execute migration strategies from legacy systems to the new platform • Ensure business continuity while building the future state architecture • Collaboration and Leadership • Work closely with data analysts, data scientists, product managers, and business stakeholders to understand needs and translate them into technical solutions • Mentor junior engineers and contribute to the growth of the data engineering practice • Communicate technical concepts clearly to both technical and non-technical audiences • Leverage AI for Development • Use AI tools (including Claude, GitHub Copilot, etc.) to accelerate development and improve productivity—we care about outcomes, not how you get there • Maintain regular and reliable attendance, including being present, on time, and prepared for work as scheduled