The Senior Data Architect will design and oversee the implementation of end-to-end data solutions while accelerating the company's data modernization strategy. This role involves collaborating with stakeholders to define scalable architecture patterns and providing hands-on leadership for high-priority data initiatives.
Lead cloud infrastructure design and migration efforts on AWS while developing scalable Django-based applications. Act as a technical advisor to stakeholders and mentor junior engineers while championing engineering best practices.
Design, develop, and deploy end-to-end machine learning models and pipelines to drive business value. Collaborate with cross-functional teams to implement MLOps practices and optimize model performance in production.
Build and lead the talent acquisition function from the ground up, designing scalable recruiting processes and hiring strategies for India and the USA. Manage a team of recruiters and sourcing specialists while partnering with senior leadership to execute workforce planning and bulk hiring.
Design and own the architecture of Databricks-based data platforms, including lakehouse design and medallion architecture. Lead complex data engineering initiatives and integrate AI/ML capabilities such as RAG and feature engineering pipelines.
Proactively source and pipeline exceptional candidates for engineering, operations, and corporate functions across India and US markets. Manage the full candidate lifecycle from initial screening and interview coordination to maintaining ATS data hygiene.
Design, build, and optimize production-grade data pipelines and analytics solutions to support business intelligence and AI/ML initiatives. Manage data infrastructure on Snowflake and Databricks while implementing DataOps and data observability practices.
Lead the design and delivery of production-grade data platforms, pipelines, and analytics solutions to drive business intelligence and AI/ML capabilities. You will own critical data workstreams end-to-end, managing architectural decisions and mentoring other engineers.
Design, build, and operate cloud infrastructure and DevOps workflows across AWS and Azure. Drive CI/CD maturity, manage containerized workloads, and optimize cloud costs and security.
Define and lead the long-term technical vision and architecture for the organization's AI/ML platform and MLOps capabilities. Solve complex technical problems and mentor senior engineers to ensure scalable, enterprise-grade ML systems.
Lead the design and implementation of scalable AWS cloud infrastructure and Django-based applications. Act as a technical advisor to stakeholders while managing cloud migrations, CI/CD pipelines, and platform engineering solutions.
Design, build, and deploy machine learning models and end-to-end ML pipelines to drive business value. Implement MLOps practices and collaborate with cross-functional teams to integrate ML solutions into production services.
Lead the design and implementation of scalable AWS cloud infrastructure and Django-based applications. Act as a technical advisor to stakeholders while managing cloud migrations, CI/CD pipelines, and platform engineering solutions.
Design, build, and operate cloud infrastructure and DevOps workflows on AWS and Azure. Drive CI/CD maturity, manage containerized workloads, and optimize cloud costs and security.
