Senior Data Architect

We are looking to hire a Senior Data Architect to help define, mature, and scale our enterprise data architecture. This role will focus on designing trusted, well-governed, reusable, and scalable data assets that support business operations, reporting, analytics, data products, system integration, and emerging AI use cases.

The Senior Data Architect will partner with data engineering, application teams, analytics, security, governance, AI/ML, and business stakeholders to establish practical architecture standards, improve data usability, and ensure critical data sources are well-modeled, documented, discoverable, secure, and fit for purpose.

This role is critical to building a strong data foundation that enables consistent decision-making, operational efficiency, advanced analytics, and future-ready technology capabilities.

Key Responsibilities and Essential Functions

• Define and maintain data architecture standards, principles, patterns, and best practices across key business and data domains.
• Assess and rationalize critical data sources based on business value, quality, ownership, usage, sensitivity, lifecycle, and strategic importance.
• Design conceptual, logical, and physical data models that support operational systems, analytical platforms, reporting, data products, and integration needs.
• Establish reusable data structures, canonical data models, reference data patterns, and integration approaches to improve consistency across systems.
• Define architecture patterns for data ingestion, transformation, storage, consumption, sharing, retention, and lifecycle management.
• Partner with data engineering teams to translate architecture into scalable pipelines, curated datasets, data marts, reusable services, and platform-ready data assets.
• Drive standards for metadata, lineage, business definitions, data ownership, data quality rules, documentation, and data observability.
• Support governance practices by helping define how data should be classified, secured, cataloged, retained, and accessed.
• Work with application and platform teams to improve interoperability across source systems, APIs, data warehouses, data lakes, lakehouses, and cloud platforms.
• Guide teams in designing reusable and trusted data assets that can serve multiple consumption patterns, including reporting, analytics, automation, machine learning, and AI-enabled solutions.
• Provide architecture guidance during solution design, data quality investigations, platform modernization, and data integration initiatives.
• Communicate architecture decisions, tradeoffs, standards, and design recommendations clearly to technical teams and senior stakeholders.
• All other duties as assigned

• Bachelors with 7+ (or Masters with 5+) years of relevant experience in data architecture, data modeling, data engineering, data integration, analytics architecture, or related data disciplines
• Strong experience designing data architectures across operational systems, analytical platforms, data warehouses, data lakes, lakehouses, and cloud-based data ecosystems.
• Deep understanding of data modeling techniques, including conceptual, logical, and physical modeling, dimensional modeling, canonical modeling, and domain-oriented modeling.
• Proven ability to design trusted, governed, reusable data assets for business operations, reporting, analytics, data integration, and data product use cases.
• Strong knowledge of data quality, metadata management, lineage, cataloging, master data, reference data, and access control practices.
• Experience defining architecture patterns for batch, near-real-time, API-driven, and event-driven data integration.
• Experience working with modern cloud and data platforms such as Snowflake, Databricks, Azure, AWS, GCP, Informatica, dbt, or similar technologies.
• Ability to collaborate effectively across data engineering, application, analytics, security, governance, AI/ML, and business teams.
• Strong communication skills with the ability to explain complex data concepts to senior technical and business stakeholders.
• Ability to balance long-term architecture direction with practical implementation guidance.
• Experience creating architecture artifacts such as data flow diagrams, domain models, source-to-target mappings, architecture decision records, and data standards documentation.

Preferred

• 10+ years of experience in data architecture, data modeling, data engineering, data integration, analytics architecture, or related data disciplines
• Experience supporting AI, machine learning, generative AI, LLM, RAG, or AI assistant initiatives as downstream consumers of governed data assets.
• Familiarity with AI-enabling data concepts such as semantic layers, embeddings, vector databases, semantic search, knowledge graphs, or ontology design.
• Experience with data product thinking, domain-oriented data ownership, or data mesh concepts.
• Experience in regulated environments with privacy, security, compliance, audit, or data protection requirements.
• Experience with platform modernization, migration from legacy data platforms, or simplification of complex data ecosystems.

Salary Range: $132,000 - $198,000