Strategic Leadership

• Define and execute a transformative vision for our data platform architecture that scales to billions of daily events

• Partner with CTO and engineering leadership to align platform strategy with business objectives

• Drive adoption of next-generation technologies including vector databases and ML-powered analytics

• Build strategic roadmaps that balance innovation with operational excellence

Technical Architecture

• Lead the evolution from current state to a modern, cloud-native data platform with embedded ML/AI capabilities

• Work with the team to deliver fault-tolerant, multi-region architectures supporting real-time and batch processing

• Build and maintain the services, platforms, and frameworks enabling Samba’s data engineering teams

• Architect embedding-based systems for content understanding, viewer similarity, and semantic search

• Deliver  infrastructure for vector storage, indexing, and retrieval at scale (billions of embeddings)

• Champion best practices in data governance, security, and compliance (GDPR, CCPA)

• Evaluate and implement emerging technologies (streaming architectures, lakehouse patterns, ML platforms)

ML/AI Infrastructure

• Design platforms for embedding generation, storage, and serving at scale

• Implement vector search capabilities for real-time recommendations and content discovery

• Build infrastructure supporting multimodal embeddings (video, audio, text metadata)

• Enable self-service ML capabilities for data scientists and analysts

• Establish MLOps practices for embedding model lifecycle management

Team & Organizational Development

• Build and mentor a world-class team of platform engineers, ML engineers, and architects

• Foster a culture of innovation, experimentation, and continuous learning

• Establish clear career paths and growth opportunities for team members

• Drive cross-functional collaboration with data science, product, and engineering teams

Operational Excellence

• Establish SLAs and monitoring frameworks for internal and external clients

• Provide observability tools for Data Engineering and Data Science, including tools to enforce data quality

• Lead vendor relationships and technology partnerships

• Drive automation and self-service capabilities for internal customers

• 12+ years in data platform/infrastructure roles, with 5+ years in senior leadership

• Proven track record of leading large-scale platform transformations

• Experience building production embedding systems and vector databases

• History of building and scaling teams of 20+ engineers

• Deep expertise in modern data architectures (data mesh, lakehouse, streaming-first)

• Proficiency with, Stream processing (Kafka, Flink, Spark Streaming), Modern data warehouses/lakes (Snowflake, Databricks, BigQuery), Workflow management (Airflow, etc), Container orchestration (Kubernetes, EKS/GKE), Infrastructure as Code (Terraform, CloudFormation), ML platforms (MLflow, Kubeflow, SageMaker)

• Exceptional communication skills to articulate complex technical concepts to diverse audiences

• Strategic thinking with ability to balance long-term vision with short-term deliverables

• Strong business acumen to connect technical decisions with business outcomes

• Track record of influencing without authority across organizational boundaries

• Knowledge of privacy-preserving analytics and clean room technologies

• Contributions to open-source projects in ML infrastructure or vector search

• Advanced degree in Computer Science, Machine Learning, or related field