Staff Data Engineer

Role overview Set technical direction for enterprise data platforms and lead their design and delivery across lakes, warehouses, and pipelines. The role combines hands-on engineering with architecture decisions, platform modernization, and mentorship, including data foundations for production AI and machine learning systems.

Responsibilities - Design and build scalable data architectures and batch or streaming pipelines, balancing reliability, security, performance, and cost. - Establish data quality, governance, compliance, and data contract practices across platforms and teams. - Develop pipeline monitoring, alerting, deployment automation, and integrations with APIs and external systems. - Build data flows for AI and ML workloads, including embeddings, vector stores, retrieval-augmented generation, feature stores, and training or inference data. - Guide platform strategy with technical and business stakeholders, make consequential architecture decisions, and mentor other engineers. - Set engineering standards and collaborate with product, analytics, AI, backend, and platform teams.

Requirements - At least seven years of data engineering experience, including leadership of complex platform initiatives. - Strong distributed systems and architecture background, with expertise in cloud data platforms, warehouses, orchestration, and data modeling. - Expert skills in Python, Scala, and SQL; experience with streaming systems and real-time processing. - Experience with governance, data quality, container orchestration, and CI/CD for data systems. - Demonstrated delivery of production AI/ML data pipelines and practical expertise with AI-assisted coding tools. - Technical leadership, mentoring, stakeholder communication, and sound judgment in ambiguous situations.

Nice to have - Experience with data mesh or fabric, lakehouse architectures, or governance framework implementation.