Lead the architecture and development of core data platform capabilities, including processing frameworks, storage patterns, and shared services
Design and implement multi-tenant, multi-cloud data systems with strong isolation, scalability, and operational durability
Build and operate large-scale distributed data processing systems across batch and real-time workloads
Define and evolve data lifecycle patterns, including ingestion, validation, transformation, enrichment, and serving
Establish data quality gates and validation frameworks to ensure trust, consistency, and auditability
Design systems that integrate with platform infrastructure, including CI/CD, deployment orchestration, observability, and infrastructure automation
Make sound architectural decisions across performance, cost, reliability, and maintainability tradeoffs
Lead ambiguous, high-impact initiatives where both problem definition and solution design require ownership
Contribute significantly to production code, setting standards for quality, testing, and operability

10+ years of experience building data-intensive or distributed systems, with a strong software engineering foundation
Proven experience designing and operating large-scale data platforms in production
Deep expertise in distributed data processing systems (e.g., Spark or similar big data technologies)
Strong software engineering fundamentals, including system design, testing, CI/CD, and production debugging
Experience building systems in cloud environments (AWS preferred), including storage, compute, and security patterns
Experience designing multi-tenant systems, with a focus on isolation, scalability, and reliability
Strong understanding of data modeling, pipeline design, and data quality enforcement
Ability to navigate ambiguity, evaluate tradeoffs, and drive durable technical decisions
Track record of being a high-impact, hands-on contributor who leads through both design and execution

Staff Data Engineer, Platform Engineering

Key skills