Lead Data Engineer

Role Overview: As a Lead Data Engineer at Searce, you will be at the forefront of architecting and leading the development of scalable, cloud-native data platforms. Your role will involve guiding the team on critical architectural decisions, building high-velocity data pipelines, mentoring and elevating the squad, driving AI-ready data strategy, partnering with clients as a Technical DRI, troubleshooting and optimizing for scale, and innovating to build reusable IP. Key Responsibilities: - Lead Technical Design & Data Architecture: Architect and lead the end-to-end development of scalable, cloud-native data platforms. Guide the squad on critical architectural decisions and contribute high-quality, production-grade code. - Build High-Velocity Data Pipelines: Drive the implementation of robust data transports and ingestion frameworks using Python, SQL, and Spark. Build integration layers connecting heterogeneous sources into unified, high-availability environments. - Mentor & Elevate the Squad: Foster a culture of technical excellence by mentoring and inspiring a team of data analysts and engineers. Lead deep-dive code reviews and promote best-practice data modeling. - Drive AI-Ready Data Strategy: Design data foundations optimized for AI and Machine Learning. Champion the use of GCP and AWS to create environments for advanced analytics and generative AI models. - Partner with Clients as a Technical DRI: Act as the Directly Responsible Individual for client success. Translate business questions into data services, manage project deliverables, and ensure data accuracy. - Troubleshoot & Optimize for Scale: Own the reliability of the reporting layer. Proactively monitor pipelines, troubleshoot bottlenecks, and propose improvements for platform performance. - Innovate and Build Reusable IP: Spearhead the creation of reusable data frameworks and transformation libraries that accelerate future projects and establish technical advantage in the market. Qualifications Required: - Engineering Depth: 7-10 years of professional experience in end-to-end data product development with a portfolio showcasing complex, high-velocity pipelines for Batch and Streaming workloads. - Cloud-Native Fluency: Deep, hands-on experience designing and deploying scalable data solutions on major cloud platforms like AWS, GCP, or Azure. - AI-Native Workflow: Proficiency in using AI coding assistants to accelerate delivery and building data foundations for Generative AI. - Architectural Portfolio: Evidence of leading large-scale transformations including platform migrations, data lakehouse builds, or real-time analytics architectures. - Client-Facing Acumen: Direct experience in a consultative, client-facing role, with the ability to translate business vision into technical specifications. Role Overview: As a Lead Data Engineer at Searce, you will be at the forefront of architecting and leading the development of scalable, cloud-native data platforms. Your role will involve guiding the team on critical architectural decisions, building high-velocity data pipelines, mentoring and elevating the squad, driving AI-ready data strategy, partnering with clients as a Technical DRI, troubleshooting and optimizing for scale, and innovating to build reusable IP. Key Responsibilities: - Lead Technical Design & Data Architecture: Architect and lead the end-to-end development of scalable, cloud-native data platforms. Guide the squad on critical architectural decisions and contribute high-quality, production-grade code. - Build High-Velocity Data Pipelines: Drive the implementation of robust data transports and ingestion frameworks using Python, SQL, and Spark. Build integration layers connecting heterogeneous sources into unified, high-availability environments. - Mentor & Elevate the Squad: Foster a culture of technical excellence by mentoring and inspiring a team of data analysts and engineers. Lead deep-dive code reviews and promote best-practice data modeling. - Drive AI-Ready Data Strategy: Design data foundations optimized for AI and Machine Learning. Champion the use of GCP and AWS to create environments for advanced analytics and generative AI models. - Partner with Clients as a Technical DRI: Act as the Directly Responsible Individual for client success. Translate business questions into data services, manage project deliverables, and ensure data accuracy. - Troubleshoot & Optimize for Scale: Own the reliability of the reporting layer. Proactively monitor pipelines, troubleshoot bottlenecks, and propose improvements for platform performance. - Innovate and Build Reusable IP: Spearhead the creation of reusable data frameworks and transformation libraries that accelerate future projects and establish technical advantage in the market. Qualifications Required: - Engineering Depth: 7-10 years of professional experience in end-to-end data product development with a portfolio showcasing complex, high-velocity pipelines for Batch and Streaming worklo