Manager, Software Engineering, Data Platform

Responsibilities: Define and own the vision, architecture, and roadmap for ingestion, orchestration, warehouse, BI, and real-time data services Manage and grow senior engineers, coaching ICs into technical leaders Lead AI-agent management, guardrails, and output quality standards Govern datasets with provenance, labeling workflows, access controls, and reproducibility Enhance platform with AI-assisted tooling and agentic capabilities for design, coding, testing, and on-call Ensure data quality through SLOs, data contracts, lineage, and automated checks Develop self-service onboarding for sources, pipelines, dashboards, and monitoring rules Maintain a reliable production platform with SLAs, cost attribution, budgeting, and vendor rollback plans Collaborate cross-functionally to build reusable platform capabilities, not one-off pipelines Stay involved in design reviews, debugging, and prototyping to accelerate progress

Key requirements: 4+ years of people management for software engineers; 6+ years in data, ML, or platform engineering deep data platform experience with warehouse, orchestration, streaming, or ingestion at scale defined data SLOs and data quality improvements; ability to adjust architecture when data reliability is compromised familiarity with AI/LLM-based data systems and agentic data workflows; enforce data access controls experience building self-service platforms and driving adoption across teams hands-on capability to read and critique code/designs and ship production code clear communication of complex systems to diverse stakeholders understanding of model training/evaluation, data labeling, and provenance to reduce bias/leakage leadership and coaching clear communication collaboration across diverse teams data ingestion and orchestration platforms (e.g., Airflow, Pub/Sub, Kafka, Iceberg) warehouse engineering and real-time data processing AI/agentic data systems and evaluation frameworks