Data Engineer
Data Contract and Metadata Standards
Implement and maintain data contract specifications that codify table ownership, schema expectations, and quality thresholds; enforce standards through automated validation in the deployment pipeline; collaborate with data owners to improve metadata coverage across the team's data estate.
AI Readiness Scoring
Contribute to an automated scoring pipeline that evaluates data assets on their readiness for AI and analytical use; build and maintain the jobs that collect quality signals and surface scores to data teams.
AI Governance and Compliance
- Support the discovery and classification of sensitive data across the data estate.
- Maintain tagging and lineage automation frameworks.
- Help translate data access and privacy policies into practical guardrails in partnership with the platform team.
- Monitor AI usage across the company, defining new avenues for AI assistance.
AI Trust and Reliability
- Build the systems that make people actually trust what the AI tells them about our data, such as query accuracy checks, guardrails that keep AI tools on certified data, and clear attribution so users can see where an answer came from.
- Make sure we have the monitoring in place to catch problems before they erode confidence.
Semantic Layer Contributions
Build and maintain the semantic framework that make data assets more legible to both people and AI systems, adding descriptions, context, and query guidance that improve the accuracy of natural language queries; work with analysts and domain experts to capture and formalize business definitions.
AI-Augmented Development
- Proactively leverage AI tools (e.g., Claude, Databricks Genie) to accelerate development, maintain code quality, and explore new approaches to data engineering problems.
Cross-team Collaboration
- Partner with adjacent teams to onboard data assets into the AI-ready platform, document processes and contribute to the team's shared knowledge base.
Core Values
- Integrity
- Boldness
- Ownership
- Teamwork
- Transparency