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About Sovrn Every interesting company solves important problems for other people.  Sovrn is a Software and Data business that helps Open Web businesses be and remain independent.  We help them understand their business better, operate more efficiently, and make & keep more money. We believe  in the freedom and free-flow of information. We believe  the Open Web is the largest source of this information. We believe  in helping Open Web businesses be and remain Independent. Through Software products and Data solutions we help our customers: Understand their business better , so they can make better decisions Operate   their business more efficiently,  so they can invest in what matters most Make (and Keep)   more money , so they control their own destiny 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. You'll be working with a strong senior team, a modern stack, and an organization that already uses LLMs and agentic tooling across the data stack. We're looking for a leader who can take what's working from "in use" to "intentional practice." Someone with strong opinions about what high-leverage AI-native data engineering looks like at exchange scale, and the credibility to bring the rest of the org along. Languages / components / tools in our stack: Python, Redpanda/Kafka, Databricks/Spark, AWS/S3, Terraform, Datadog, GitHub What you'll be doing: 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 Heavily contribute to the design and architecture of Sovrn's data pipelines, lakehouse, and data services: 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 improve