Senior Principal - Data Engineering

Overview

This role focuses on providing deep expertise in designing and implementing enterprise-scale Data Lakehouse architectures. It centers on developing scalable data platforms and robust big data frameworks that enhance analytics, business intelligence, AI, and data-driven decision making across the organization.

Key Responsibilities

• Craft and direct the Data Lakehouse architecture aligned with business and technology goals.
• Develop standards, engineering guidelines, and roadmaps for enterprise data platforms.
• Assess new big data technologies to recommend solutions aligned with strategy.
• Maintain scalability, reliability, and performance of Data Lakehouse systems.
• Manage and update the enterprise data catalog to improve data discoverability and classification.
• Lead design and building of scalable data pipelines supporting analytics and reporting.
• Set standards for data ingestion, transformation, and integration pipelines ensuring reliability and efficiency.
• Optimize performance and scalability by diagnosing and resolving processing bottlenecks and driving capacity planning.
• Define and enforce engineering standards, best practices, and governance aligned with security and compliance.
• Support data governance through thorough management of data references and documentation.
• Empower platforms to support business intelligence, advanced analytics, AI, and machine learning by collaborating with relevant teams.
• Serve as the organization’s expert in Data Lakehouse technologies, offering mentorship and technical leadership to teams.
• Lead technical delivery of major data initiatives, managing risks, dependencies, and aligning outputs with business needs.
• Adhere strictly to departmental policies, safety, and information security standards ensuring data integrity and a safe workplace.

Qualifications and Experience

• Bachelor’s degree in Computer Science, Data Engineering, IT, Software Engineering or a related field.
• At least 10–12 years of experience in Data Engineering, Big Data platforms, Data Architecture, Business Intelligence or Analytics domains.