Director, Data Collective

About The Role

We're looking for a Director, Data Collective to lead the team that owns Sovrn's data platform end-to-end: the pipelines, lakehouse, data services, and cloud infrastructure that power our exchange, our products, and our customers' decisions. This is a hands-on engineering leadership role. You'll own team composition and hiring; lead architecture and design across the platform; and remain close enough to the code, the systems, and the tradeoffs to make real technical decisions, not just approve them.

• Team Leadership & Composition
• Own the skill mix of the Data Collective team; lead hiring and performance management for engineers ranging from mid-level to Principal
• Set the technical and cultural standards for the team: what "great" looks like in design, code review, on-call, and cross-team partnership
• Mentor and grow engineers across levels through hands-on design collaboration, technical coaching, and clear career frameworks
• Partner with the broader engineering leadership team on org-wide planning, budgeting, and roadmap tradeoffs; represent the team's work and constraints to executives

Data Platform Architecture & Engineering

• Drive architectural decisions across pipeline design, data modeling, lakehouse architecture, and data services layers
• High-throughput streaming, always-on batch, petabyte-scale storage and query
• Lead design reviews and set technical standards across the team; raise the bar on engineering rigor, observability, and operational excellence
• Stay close enough to the systems to make real tradeoffs on performance, cost, governance, and reliability, and to know when the team's estimates and risk assessments are right

AI & Modern Data Engineering Practice

• Set the team's direction on AI-native data engineering: where LLMs, RAG, agentic workflows, and AI-assisted tooling create real leverage in a high-throughput adtech environment, and where they don't
• Establish standards for how the team evaluates, trusts, and operates AI-powered systems in production: observability, fallback behavior, model governance, and cost control
• Identify high-leverage AI applications in the data stack: intelligent pipeline optimization, anomaly detection, automated data quality, forecasting, and LLM-powered data services

Operational Excellence & Cost Management

• Own the operational posture of the data platform: SLOs, on-call health, incident response, and continuous improvement
• Own the infrastructure cost footprint of the Data Collective across AWS and Databricks; drive structural cost improvements through architecture, and disciplined commitment management
• Drive Infrastructure as Code (IaC) adoption, policy-as-code, governance frameworks (RBAC/ABAC, IAM, SCIM), and CI/CD for infrastructure across the team
• Make sure the team is investing in the right balance of new capability, platform health, and tech debt

Cross-functional Collaboration

• Provide domain expertise across the organization to enable business growth through data services and data models
• Partner with Product, Data Science, AI/ML, Platform, and Security teams to ship end-to-end and to make Sovrn's data assets easier and safer to use
• Serve as a senior point of counsel to all consumers and stakeholders of Sovrn's data: internal teams, leadership, and external customers of our Data-as-a-Service products
• Communicate clearly at multiple levels: from architecture documents and design reviews to executive updates on cost, capacity, and risk