Senior Data Architect – Hands on

Job not on LinkedIn

🕒 June 18

🇺🇸 United States – Remote

⏰ Full Time

🟠 Senior

🚰 Data Engineer

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Stratus

WebsiteLinkedInAll Job Openings

501 - 1000 employees

Founded 2001

🤝 B2B

🏢 Enterprise

🤖 Artificial Intelligence

B2B • Enterprise • Artificial Intelligence

Stratus is a B2B technology and consulting firm that helps property & casualty insurers and Managing General Agents modernize legacy core systems, migrate to the cloud, and transform insurance data to enable faster product launches, better analytics, and operational efficiency. It offers domain-focused services including Guidewire and Insurity implementation and optimization, cloud migration roadmaps on Azure, AI readiness and execution, data strategy and governance, application maintenance and QA, platform selection support, and on-demand IT talent via embedded delivery pods. Stratus positions itself as a high-touch partner delivering practical, people-first modernization and talent solutions for insurance technology transformation.

📋 Description

• Own our canonical data architecture — the schema, contracts, tenancy, and governance. • Make production data AI-ready: well-modeled, contract-enforced, lineage-tracked, and drift-detectable. • Own the canonical data model — the normalized definition of the core business objects shared across our products. • Define the multi-tenant data architecture: tenancy isolation, data residency posture, and per-tenant cost attribution. • Lead staged modernization toward the right mix of stores and patterns. • Own the architectural direction of the data pipeline and lake / lakehouse layer. • Drive hands-on prototypes, reference implementations, and in-repo guardrails. • Partner with database engineering on production data health while owning long-term architectural direction.

🎯 Requirements

• 8+ years in data architecture, data engineering, database administration, or analytics engineering, with 3+ years in senior / lead roles. • Demonstrated ownership of a canonical or enterprise data model / cross-product schema. • Hands-on MongoDB at production scale (Atlas M40+ ideal): document modeling, aggregation framework, indexing, change streams, sharding, replica sets. • Strong polyglot-persistence judgment. • Hands-on relational depth: schema design, indexing strategy, and query tuning. • Production experience making data AI/ML-ready: data architecture supporting RAG, semantic search, embeddings / vector pipelines, or agentic workloads. • Multi-tenant architecture experience: data residency and per-tenant cost attribution. • Pipeline / ELT / lake / lakehouse design at scale, with incremental migration strategies that minimize disruption. • Cloud-native data services (Azure, AWS, or GCP). • Strong grasp of data quality, testing, lineage, and monitoring.

🏖️ Benefits

• Comprehensive and competitive health benefits plan • Matching 401k contributions • 20 days annual PTO • Primarily remote work with occasional annual team onsites