Lead Specialist, Data Lakehouse

1. Why This Role Matters

The Lead Specialist, Data Lakehouse II enables the organization to maximize the value of enterprise data by developing and optimizing scalable data lakehouse platforms that support analytics, artificial intelligence, automation, and digital transformation initiatives. The role creates a trusted foundation for data-driven decision-making across business and operational functions.

The role drives the design, integration, and continuous improvement of modern data architectures that improve data accessibility, quality, reliability, and performance. By strengthening enterprise data capabilities, the role accelerates innovation, improves business insights, and supports the delivery of strategic Technology and Innovation objectives.

As a key technical specialist within Data & AI, the role ensures that data platforms remain secure, scalable, governed, and aligned with evolving business and technology requirements while enabling advanced analytics and AI use cases.

• Deliver scalable lakehouse architecture solutions that support enterprise analytics, reporting, AI, and machine learning initiatives.
• Translate business and platform requirements into sustainable data engineering and architecture solutions.
• Align data platform capabilities with organizational digital transformation and technology strategies.

• Optimize data ingestion, processing, storage, and transformation capabilities to improve platform efficiency and performance.
• Strengthen platform reliability, availability, and scalability to ensure uninterrupted access to critical business data.
• Improve data lifecycle management practices and operational efficiencies across the data ecosystem.

• Enable trusted and governed data environments through effective data quality, lineage, security, and compliance controls.
• Strengthen enterprise data standards, architecture principles, and platform governance frameworks.
• Ensure adherence to organizational policies, security requirements, and regulatory obligations.

• Drive the adoption of modern data technologies, engineering practices, and architectural standards.
• Evaluate emerging technologies and recommend enhancements that improve platform capability, scalability, and business value.
• Accelerate the deployment of advanced analytics and AI solutions through robust data platform capabilities.

• Build strong partnerships with business, analytics, architecture, cybersecurity, and technology teams to deliver integrated solutions.
• Provide technical guidance and expertise on data platform strategy, architecture, and implementation.
• Strengthen organizational capability through knowledge sharing, mentoring, and adoption of best practices.

• High availability, reliability, and performance of enterprise data lakehouse platforms.
• Improved accessibility, quality, and consistency of enterprise data assets.
• Faster delivery of analytics, reporting, AI, and data-driven business solutions.
• Strong compliance with data governance, security, and architecture standards.
• Increased scalability and operational efficiency of data platforms.
• Successful adoption of modern data technologies that generate measurable business value.

• Bachelor's degree in Computer Science, Information Systems, Data Engineering, Software Engineering, or a related discipline.

• 8–12 years of relevant experience in data engineering, data platforms, data lakehouse, or enterprise data management environments.
• Experience designing and implementing large-scale cloud and modern data architecture solutions.
• Experience delivering enterprise analytics, data integration, and AI-enabling platforms.
• Experience leading complex technical initiatives and collaborating across multiple business and technology functions.

• Data Lakehouse Architecture
• Data Engineering & Integration
• Cloud Data Platforms
• Data Modeling & Data Management
• Data Governance & Security
• Advanced Analytics and AI Enablement
• Business & Delivery

• Solution Architecture
• Project & Program Delivery
• Technology Optimization
• Risk & Compliance Management
• Performance Improvement
• People & Collaboration

• Influencing and Communication
• Cross-functional Collaboration
• Technical Leadership
• Knowledge Sharing & Mentoring
• Problem…