- Own the end-to-end design, delivery, and operation of major data products, including high-throughput ETL/ELT pipelines, transformation workflows, and storage solutions.
- Partner with engineering, product, and business stakeholders to define requirements and drive projects from design through production.
- Develop performance-tuned transformations and services using Python, SQL, and dbt.
- Author technical designs and RFCs communicating architecture, risks, and operational considerations.
- Lead projects improving engineering excellence, such as data observability, lineage, incident response, and deployment safety.
- Design and operate scalable batch and real-time data solutions using technologies such as Spark, Flink, and Kafka.
- Partner with the ML Platform team to deliver datasets for model training and inference.
- Participate in the team's on-call rotation, responding to incidents, troubleshooting issues, and contributing to root cause analysis.