Senior Staff Enterprise Architect, Data

Key Responsibilities

Data Strategy & Roadmap

• Design semantic layer architecture standardizing business metrics enterprise-wide. Define governance guardrails ensuring natural language queries access validated master data sources.
• Develop Master Data strategy for Customer and Product domains (phases 1-2), Finance and People to follow. Define golden record requirements, stewardship models, and system-of-record hierarchy.
• Define cross-cloud data integration strategy and reference architecture. Specify patterns (federation, replication, abstraction layer) balancing performance, cost, and data freshness.
• Develop 12-24 month data architecture roadmaps for Finance, Sales, Product, and People.

Systems Design & Solution Leadership

• Evaluate AI-powered data observability platforms for quality monitoring, pipeline failure prediction, and data classification.
• Define data ingestion architecture reducing availability from weeks to 3-5 days (batch) and under 15 minutes (real-time).
• Establish build vs. buy frameworks for Data Platform, ETL, Data Quality, and Master Data tooling.
• Design data solutions for priority initiatives (customer 360, financial reporting, AI pipelines).
• Apply product thinking to data platforms, treating internal consumers as customers.
• Lead solution scoping workshops, provide effort estimates, and identify dependencies.

Technical Execution & Delivery

• Participate in design reviews and checkpoints to validate alignment with architectural standards.
• Serve as early adopter of MongoDB Atlas and Voyage AI (including vector search for RAG).

Governance, Standards & Risk Management

• Define data lineage strategy and technical requirements.
• Design automated data quality frameworks with validation rules, anomaly detection, and quarantine workflows.
• Collaborate with InfoSec on data access governance and security monitoring tools.
• Establish data architecture principles and design patterns. Chair bi-weekly architecture review board meetings.
• Conduct impact assessments for major initiatives.
• Create and maintain architecture documentation.

Team Leadership & Evangelism

• Build architecture community of practice.
• Develop data literacy enablement.
• Mentor 5-10 data engineers and architects.

Qualifications

• 12+ years in IT with 7+ years in Data Architecture, Data Engineering, or Enterprise Architecture roles.
• 10+ years across three or more: data architecture, data engineering, database management, analytics, or cloud infrastructure.
• Proven ability to architect solutions that bridge Data Lakes and Warehouses in separate clouds (e.g., AWS, Azure, Google Cloud).
• Hands-on experience with Master Data and data lineage tools.
• Experience evaluating or implementing AI/ML tools for data quality monitoring and automated data classification.
• Proven success reducing data latency using CDC, streaming, or real-time integration patterns.
• Proficient in SQL and Python. Experience with modern data platforms (Snowflake, Databricks, BigQuery, or similar). RAG architectures and vector databases are a plus.
• Led architecture for large-scale implementations: CRM, Enterprise Data Platforms, Data Lakes, or ERP systems.
• Experience managing vendor evaluations, contract negotiations, and ongoing partner relationships.
• Experience and understanding of MongoDB products and capabilities is a plus.
• Bachelor's degree in computer science, computer engineering, electrical engineering, systems analysis, or a related field; MS or advanced degree is preferred.