Senior Data Architect

No C2C or H1B, OPT-EAD or F1 Visas. The Data Architect will serve as a strategic and enterprise-level leader, responsible for defining the long-term data architecture vision and enabling a modern, scalable, and AI‑ready data ecosystem. This role focuses on strategy, architecture leadership, and cross‑organizational influence, not hands‑on engineering execution. The architect will guide teams across the business and technology landscape to modernize data platforms, strengthen governance, and prepare the enterprise for AI‑driven decision-making. Key Responsibilities Strategic Architecture Leadership • Develop and maintain a future-focused data architecture roadmap aligned with business strategy and enterprise modernization goals. • Define future-state architectures supporting analytics, machine learning, MLOps, and intelligent automation across the organization. • Translate business needs into data solutions with clear, measurable outcomes. Data Platform & AI Enablement • Design and evolve cloud-native data platforms, including data warehouses, data lakes, and Lakehouse architecture. • Architect systems that support advanced analytics and future AI initiatives; deep ML expertise is not required but awareness and willingness to grow is essential. • Lead evaluations, proof-of-concepts, and architectural whiteboarding to explore transformational opportunities. Governance, Quality, and Ethics • Establish and enforce frameworks for data governance, data quality, privacy, lineage, and responsible AI. • Ensure compliance with regulatory requirements and ethical standards for data and AI use. Cross‑Functional Collaboration & Influence • Partner with enterprise architects, data engineers, developers, and business leaders to drive alignment and execution of architectural direction. • Provide architectural oversight and mentor teams in modeling, integration patterns, and best practices. • Communicate complex concepts to both technical and non-technical audiences to drive adoption. Solution Integration & Delivery Support • Guide the integration of data platforms with microservices, event-driven architectures, and external partner systems. • Support engineering teams with architectural validation and high-level design reviews (non-hands-on). Required Qualifications Technical Expertise • 5+ years leading enterprise data architecture initiatives. • Strong proficiency in data modeling, distributed data systems, warehouse/lake/Lakehouse design, and data integration patterns. • Experience with Snowflake or similar cloud data platforms (Databricks, Redshift, Synapse, BigQuery). • Experience with MongoDB or other NoSQL document databases. • Familiarity with event-driven architectures such as Kafka or equivalent tools. • Proficiency in Python, SQL, cloud platforms (AWS preferred; Azure/GCP acceptable). • Knowledge of ETL/ELT methodologies supporting operational and analytical workloads. Strategic & Soft Skills • Exceptional communication skills with the ability to explain architectural decisions to business leaders. • Proven ability to influence engineering and enterprise teams without direct authority. • Strong strategic thinking, roadmap development, and decision-making abilities. • Comfortable working in Agile environments and collaborating across release trains. Preferred Qualifications • TOGAF or similar architecture certification. • Experience in insurance, benefits, or financial services. • Familiarity with MLOps, data mesh, AI governance, and real-time analytics. Ideal Candidate Snapshot A forward-thinking Data Architect who blends strategic vision, enterprise data architecture expertise, strong communication, and cross-functional leadership, while helping the organization accelerate its transition to a modern, AI-enabled data ecosystem. What This Role Is NOT • Not a hands-on developer or data engineer. • Not focused on daily coding or tactical execution. • Not suited for candidates without strategic thinking or enterprise architecture experience.