• Facilitate, guide, and influence the client and teams towards an effective architectural pattern and becoming an interface between business leadership, technology leadership and the delivery teams. • Designing of solution architecture on Google Cloud • Implementation of Proof of Concept (POC) and Minimal Viable Product (MVP) workloads. • Design a data platform that accounts for the implementation of: • Database objects • Data • Data Pipelines • Orchestration • Users and Security • Migration of workloads • Perform migration activities including: • Translation of DDL, Stored Procedures, and Queries into BigQuery and Cloud SQL supported (Postgres and MySQL) syntax • Executing data transfers using native Google Cloud and 3rd party tools • Setup and configuration of relative Google Cloud components through Infrastructure as Code (IaC) • Engage with customer teams as a Google Cloud expert to provide: • Education Workshops • Architectural Recommendations • Technology reviews and recommendations

• Design, implement, and maintain robust and scalable data pipelines using AWS, Azure, and containerization technologies. • Develop and maintain ETL/ELT processes to extract, transform, and load data from various sources into data warehouses and data lakes. • Collaborate with data scientists, analysts, and other engineers to ensure seamless data flow and availability across the organization. • Optimize data storage and retrieval performance by utilizing cloud services like AWS Redshift, Azure Synapse, or other relevant technologies. • Work with containerization tools like Docker and Kubernetes to ensure smooth deployment, scalability, and management of data pipelines. • Monitor, troubleshoot, and optimize data processing pipelines for performance, reliability, and cost-efficiency. • Automate manual data processing tasks and improve data quality by implementing data validation and monitoring systems. • Implement and maintain CI/CD pipelines for data workflow automation and deployment. • Ensure compliance with data governance, security, and privacy regulations across all data systems. • Participate in code reviews and ensure the use of best practices and documentation for data engineering solutions. • Stay up-to-date with the latest data engineering trends, cloud services, and technologies to continuously improve system performance and capabilities.

• Lead the design and evolution of the client's lakehouse/data lake architecture • Provide technical direction for the design and deployment of AI agents aimed at enabling the sales team to rapidly access fund performance insights • Define and drive the roadmap for Large Language Model adoption and Generative AI integration within the client's data ecosystem • Act as the primary technical point of contact for client leadership and senior business stakeholders • Implement and enforce DataOps principles across the data platform • Mentor and develop team members, fostering a culture of continuous learning

• Design, develop and maintain streaming data pipelines and transformations • Build and operate a big data platform used for real-time network observability and alerting • Ensure platform availability, reliability and performance • Design and implement monitoring solutions for data pipelines and platform components • Support platform evolution, upgrades and infrastructure improvements • Collaborate with internal stakeholders and translate business requirements into technical solutions • Troubleshoot complex platform and data processing issues • Create and maintain technical documentation and operational standards