Director of Engineering, Data

Platform architecture and delivery • Own the data platform end to end: ingestion, transformation, raw and sanitized data layers, and overall data architecture. • Drive data quality, observability, lineage, and governance across the organization. • Advance legacy migrations and step-change improvements to data platforms without disrupting the teams already depending on them. Enablement and adoption • Own the tooling, patterns, and support that let business domains build and maintain their own analytics and reporting under a federated ownership model. • Build the data foundations that machine learning and applied research depend on. • Drive analytics enablement for both technical and non-technical teams across the company. Org building • Hire and design the data organization as it grows over the next year. • Build and grow a world-class team of data engineering leaders.

10+ years in data engineering or data platform roles, including 5+ years in engineering management roles, currently or most recently managing managers. • Hands-on experience with modern lakehouse and streaming tooling (e.g., Databricks, Kafka, Kinesis, CDC pipelines, Airflow, Terraform) and able to contribute heavily to an architecture review with the team. • Background in high-volume, machine-generated data: telemetry, sensor, IoT, observability, or logs, rather than primarily transactional or clickstream data. • Experience running a data platform with real internal business stakeholders beyond engineering. • Experience operating in a federated or domain-ownership model, with a clear point of view on what worked and what didn't. • Experience building or substantially rebuilding platform capability, not only maintaining a mature platform.