Data Engineer II

* Design, build, and operate efficient, reliable, and well-documented data pipelines across batch and streaming systems -- from source ingestion through the warehouse to consumer-facing data products. 
* Own the data models, SLAs, and quality contracts for the domains you cover; treat documentation, testing, and observability as first-class deliverables. 
* Improve the data platform itself: introduce or extend tooling, templates, CI/CD, testing frameworks, and monitoring that make the entire team faster and more reliable. 
* Adopt and champion AI-assisted engineering -- use Claude Code and similar tools as part of your daily workflow, build internal AI-powered utilities (text-to-SQL on the semantic layer, automated PR review, log triage, data discovery), and evaluate where LLMs add durable value vs. hype.
 
* Partner directly with Data Scientists, Analysts, and business stakeholders to translate ambiguous requirements into well-scoped deliverables; communicate trade-offs, anticipate push-back, and drive alignment without needing escalation. 
* Mentor interns, new hires, and L2 engineers -- through onboarding, code review, design feedback, and pairing. 
* Contribute to cloud infrastructure and governance: IAM, service accounts, secrets management, cost optimization, and Terraform-managed GCP / Confluent Cloud resources. 
* Drive incident response and root-cause analysis for the pipelines you own; close the loop with durable fixes, runbooks, and prevention.