Director, Data Platform Engineering
Core
Lead the end-to-end architecture, delivery, and reliability of a scalable data platform enabling AI/ML, product teams, and scientists to build data-intensive applications for autonomous scientific discovery.
Role type
Director, Data Platform Engineering
Builds
A self-service data platform supporting petabyte-scale ingestion, storage, processing, and serving for analytical and machine learning workloads.
Domain
AI/ML infrastructure, scientific data processing, cloud-native data engineering
Deliverable
infrastructure
Required skills
Team leadership (8-12 engineers), technical strategy, AWS/GCP primitives (S3, Athena/BigQuery), petabyte-scale data platforms, sub-second query latency optimization, concurrent ML workload management, LLM/AI-native data patterns (vector stores, embeddings), Python, infrastructure-as-code, Kubernetes
Preferred skills
Thought leadership (conferences/blogs), open source technology growth, scientific data management, self-service product development
Technologies
Kafka, Flink, DuckDB, ClickHouse, Kubernetes, Python, AWS, GCP
Responsibilities
Build and mentor a high-performing data engineering team; Define and execute the technical roadmap for the data platform; Partner with stakeholders to understand data processing needs; Represent the platform at external conferences; Drive innovative low-code solutions for data interfaces.
Seniority
Director, hands-on IC with team leadership