Senior Data Engineer

Extensive experience building production-grade data systems in a senior or lead capacity Highly proficient in Python for building robust data processes and applications Understanding of GCP/AWS and expertise in Databricks (or similar) ecosystems Experience with streaming technologies like Kafka or Flink for near-real-time or real-time data solutions Belief in DataOps principles including CI/CD, containerization (Docker/K8s), and automated testing In-depth knowledge of database internals, data warehousing, and modern Data Lake design Sharp eye for detail and ability to explain complex technical trade-offs Naturally curious and stay ahead of industry frameworks

Architect and build scalable, high-performance data structures within GCP and Databricks Lakehouse Implement and manage low-latency solutions for near-real time analytical and product features Own end-to-end data ingestion using Airbyte + Python, transforming data into actionable datasets Sync processed data back into SaaS tools to drive business workflows and automation Evaluate and implement emerging tools and frameworks to keep the data stack at the leading edge Partner with product and engineering teams to embed data solutions into core offerings