Sr. Data Engineer - Data Modeling & Governance

Yahoo is a consumer technology company whose Yahoo Mail Data organization builds and governs large-scale data foundations that power intelligent experiences and data-driven decisions. Yahoo is seeking a Senior Data Engineer to architect enterprise data models, advance data governance and privacy practices, build AI-ready data layers, optimize distributed systems, and provide technical leadership and mentorship.

Responsibilities:

• Enterprise Data Modeling & Schema Design: Architect, optimize, and maintain Yahoo Mail’s foundational data models and schemas, delivering high-performance, cost-efficient data structures that serve multi-tenant consumers across Data Science, AI/ML, Product, and Marketing (IC5 level)
• Agentic Data Governance & Privacy by Design: Architect modern data governance methodologies for the agentic AI era—establishing formal ontologies, enterprise naming conventions, data lineage tracking, and automated quality validation engines while maintaining rigorous consumer privacy and security standards
• AI-Ready Feature & ML Modeling: Design and implement optimized data layers and vector-ready feature stores that power real-time AI/ML Mail Intelligence, downstream generative AI agents, and personalized consumer product features
• Distributed Architecture & Compute Optimization: Refine distributed data systems across cloud ecosystems (GCP/BigQuery/Dataflow), minimizing expensive analytical compute operations and maximizing query performance at massive global scale
• AI-Augmented Engineering Workflows: Champion the adoption of AI-assisted engineering tools (such as GitHub Copilot Enterprise and Anthropic Claude via AWS Bedrock) to accelerate data pipeline scripting, automate schema documentation, and detect data quality anomalies
• Architectural Judgment & Validation: Exercise expert architectural judgment in establishing safe boundaries between automated, AI-assisted code generation and deterministic data model design, preventing hallucinations and schema drift
• Cross-Functional Technical Leadership: Collaborate closely with cross-functional engineering and stakeholder teams, acting as a technical authority with Data Science leads, Principal Architects, and Product Directors across Yahoo to align data schemas with strategic business goals and analytical requirements
• Technical Stewardship & Mentorship: Chair data design reviews, establish organizational data modeling standards, and mentor senior data engineers across Yahoo Mail
• Contribute to a culture: of continuous learning and growth
• Adhering to Yahoo policies; exercising sound judgment; working effectively, safely and inclusively with others; exhibiting trustworthiness and meeting expectations; and safeguarding business operations and brand integrity

Requirements:

• Bachelor's or Master's degree in Computer Science, Data Engineering, Information Systems, or a related technical discipline (or equivalent practical experience)
• 10+ years of professional software or data engineering experience, with a proven track record of architecting and owning significant, enterprise-scale data models (IC5 level)
• Demonstrated hands-on experience utilizing AI-assisted development platforms (e.g., GitHub Copilot, Cursor, LLM-driven query engines) to accelerate architectural design, SQL authoring, and pipeline optimization
• Deep technical expertise in cloud-native distributed data architectures, data warehousing, and schema optimization at petabyte scale
• Direct experience designing data models, feature stores, and data pipelines that directly feed production AI/ML models, Data Products for Insights, recommendation engines, or LLM applications
• Proven experience defining enterprise data governance, metadata management, schema evolution, and end-to-end data lineage frameworks
• Strong familiarity with modern DevOps and infrastructure practices (CI/CD, Terraform, container orchestration)
• Hands-on expertise with Google Cloud Platform (GCP) or AWS data services at enterprise scale
• Hands-on experience with either BigQuery, Lakebase or Snowflake at enterprise scale
• Experience with Pub/Sub, Dataflow, Kafka, Apache Flink, or other streaming technologies and low latency distributed caching layers
• Experience architecting graph database structures or knowledge graphs to support entity resolution and relational data discovery
• Experience designing real-time verification frameworks or guardrails for validating AI-generated data pipelines and automated query outputs
• Familiarity with streaming architectures (Kafka, Apache Flink) and low-latency distributed caching layers
• Strong technical writing and communication skills with a track record of authoring architecture RFCs and mentoring engineering squads
• Deep knowledge of real-time data governance and AI-generated output validation
• Demonstrated abilities in prompt engineering for automating technical documentation and system architecture mapping