Data Engineer

You'll work in a modern, AI-augmented engineering environment: shipping faster with Claude Code and other AI coding assistants, building AI-powered internal tools (natural-language-to-SQL, automated data quality, lineage, anomaly detection), and bringing GenAI thoughtfully into data workflows. We expect you to take significant projects from ambiguous problem statement to delivered outcome, mentor newer engineers, and represent the team confidently with cross-functional partners.

• 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.