VP - Senior Data Engineer (Python/Snowflake/Apache Airflow)

About this role The Senior Data Engineer (VP) designs, develops, and supports enterprise-scale data platform capabilities using Airflow, dbt, Python, SQL, cloud-native technologies, and cloud data warehouse platforms to deliver scalable, reliable, and high-performance data solutions. The role focuses on building data pipelines, reusable frameworks, metadata-driven processing, data quality and governance capabilities, workflow orchestration, and platform automation, while leveraging emerging technologies such as Agentic AI to enhance engineering productivity and operational efficiency. Working closely with cross-functional teams, the engineer delivers end-to-end platform solutions, supports production operations, drives continuous improvements in platform performance and reliability, contributes to engineering best practices and platform modernization initiatives, and mentors junior engineers to foster technical excellence and continuous learning. Responsibilities Actively participate in Agile ceremonies, including requirements refinement, sprint planning, effort estimation, sprint reviews, and retrospectives, to support successful delivery of platform capabilities. Participate in technical design discussions, analyze requirements, and translate complex business needs into scalable data platform solutions. Design, develop, and optimize core enterprise data platform capabilities, including data acquisition, ingestion, transformation, workflow orchestration, and reusable processing frameworks, leveraging Python, SQL, cloud-native technologies, and cloud data warehouse platforms to support large-scale, high-performance data processing. Build and optimize large-scale data pipelines supporting data ingestion, transformation, validation, and distribution across enterprise cloud environments. Implement metadata-driven processing frameworks and reusable engineering patterns that improve automation, standardization, scalability, and reuse. Build and enhance platform capabilities related to metadata management, lineage, dependency tracking, data quality, governance, and workflow control. Incorporate Agentic AI capabilities into platform services to enhance automation, intelligent decision-making, developer productivity, and operational efficiency. Partner with cross-functional teams to support collaborative development, system integration, and end-to-end testing across platform components and dependent systems. Develop and maintain system, integration, regression, and test automation frameworks to ensure platform quality, reliability, and production readiness. Support deployment and release activities, ensuring successful rollout of platform enhancements and seamless integration with dependent systems and downstream consumers. Contribute to engineering standards, architectural patterns, operational best practices, and framework conventions that improve platform maintainability, consistency, scalability, and supportability. Provide L2/L3 production support for data platforms and products, perform root cause analysis, and implement corrective actions to ensure platform stability and operational excellence. Drive continuous improvements in platform performance, scalability, resilience, observability, and operational efficiency across data workflows and framework components. Lead Proof of Concepts (POCs) and technology evaluations to assess emerging technologies, validate architectural approaches, and identify opportunities for platform modernization and innovation. Support product documentation by providing technical expertise , implementation details, and content validation to ensure accuracy, completeness, and alignment with platform capabilities. Conduct live product demonstrations and participate in user workshops to showcase platform capabilities, gather feedback, validate solutions, and support platform adoption Required Qualifications Bachelor’s degree in Computer Science , Information Systems, or a related technical field. 8+ years