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Job Description:

Job Summary

The Senior Context Engineer is accountable for delivering enterprise data products that integrate robust data engineering with clear, business‑aligned context. This role is a cornerstone of the EDS North Star architecture, ensuring data assets are governed, discoverable, explainable, and ready for analytics and AI enablement.

The Senior Context Engineer acts as both a technical leader and a domain steward, guiding teams across data engineering, governance, and consumption layers.

Key Responsibilities

• Architect and lead development of domain‑oriented data products using EDS cloud and data platforms
• Own and drive business semantics, definitions, and contextual models for assigned data domains
• Design data solutions leveraging Databricks, BigQuery, and GCP‑native services in alignment with EDS cloud standards
• Embed governance‑by‑design, including data quality, lineage, metadata, and access controls
• Partner with analytics, data science, and AI teams to ensure data products are AI‑ready and consumption‑ready
• Support adoption of semantic layers, knowledge graph capabilities, and contextual modeling approaches
• Provide technical mentorship and architectural guidance to intermediate engineers
• Influence enterprise data platform strategy and multi‑year data maturity initiatives

Required Qualifications

• Bachelor’s degree in Computer Science, Engineering, or related field (or equivalent experience)
• 8–12+ years of experience in data engineering, analytics engineering, or data architecture
• Deep expertise in data modeling, pipeline architecture, and scalable data design
• Proven experience designing domain‑driven, reusable data products
• Hands‑on experience with cloud data platforms, preferably within GCP
• Strong understanding of metadata, lineage, data governance, and access patterns
• Strong stakeholder communication and leadership skills

Preferred Qualifications

• Experience with knowledge graphs, semantic modeling, or enterprise metadata platforms
• Familiarity with AI enablement patterns, including feature readiness and explainable data design
• Experience operating in large‑scale enterprise or regulated data environments

Role Impact Expectations

• Serve as context owner for critical enterprise data domains
• Drive alignment between data engineering, governance, analytics, and AI outcomes
• Enable scalable, trusted, and AI‑ready data products across EDS

Employee Type:
 

Permanent

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