Must Have Technical/Functional Skills
• Strong expertise in AWS Cloud services (S3, Lambda, Redshift, Glue, EMR, etc.) with enterprise solutioning experience.
• Hands-on experience in Databricks, Spark/PySpark, and modern data engineering frameworks.
• Proficiency in Python and advanced SQL for data processing and transformation.
• Experience in data ingestion, transformation, and analytics pipeline development in cloud environments.
• Good understanding of microservices, APIs, and integration patterns for scalable architecture.
• Familiarity with DevOps practices and tools (Docker, Kubernetes/EKS, CI/CD pipelines).
• Knowledge of cloud security, governance, and compliance frameworks.
• Strong experience in Agile delivery, stakeholder communication, and onsite coordination.
Roles & Responsibilities
• Lead end-to-end architecture design and solutioning for AWS-based data and analytics platforms.
• Engage with client stakeholders onsite to analyze requirements, define technical roadmap, and ensure alignment with business goals.
• Design and implement scalable data pipelines and analytics frameworks using Databricks, Spark, and AWS services.
• Define and enforce architecture standards, design principles, and best practices across application and data platforms.
• Ensure security, compliance, and robust integration design, aligned with enterprise and regulatory requirements.
• Collaborate with product, engineering, and data teams to resolve complex technical challenges and drive innovation initiatives.
• Provide technical leadership and mentorship to offshore teams, ensuring adherence to quality standards and timely delivery.
Drive effort estimation, risk management, and performance optimization to ensure predictable and efficient project
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