Senior Director - Data Platform and Cloud Services

Job description

**Samba is a media intelligence company. We know what the world is watching, reading, and thinking about — in real time, at scale, across every screen. Our data exists with the consent of over a billion people, organized into the most complete picture of consumer attention ever built. The biggest brands in the world use that picture to make smarter decisions. We think it’s the most interesting data asset on the planet, because it’s the most culturally relevant.** We're seeking a Senior Director to lead and transform our data platform and cloud services architecture. This role is not about incremental improvements – we need someone who can lead and execute a leap forward in our data infrastructure capabilities, positioning Samba at the forefront of TV data analytics and AI-driven insights. ### What you’ll do: **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 ### Who you are: - 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