Senior Data Architect

Senior Data ArchitectThe Senior Data Architect is a senior technical leader within Enterprise Data & Analytics (ED&A) responsible for defining, designing, and implementing enterprise-scale data architectures that enable trusted, governed, and business-ready data across the organization.This role requires deep hands-on expertise across transactional systems (OLTP), analytical platforms (OLAP), modern cloud data platforms, data integration, and enterprise data modeling. The Senior Data Architect is expected to operate from strategy through implementation, partnering with engineering teams to design scalable solutions while actively participating in architecture reviews, complex data modeling, performance optimization, data product design, and platform modernization initiatives.The ideal candidate brings extensive experience designing and implementing modern data ecosystems leveraging AWS, Snowflake, Data Vault 2.0, DBT, API-based integration patterns, event-driven architectures, metadata management, and AI-ready data foundations.Enterprise Data Architecture & DesignDefine and evolve enterprise data architecture standards, patterns, and reference architectures.Develop target-state architectures supporting ED&A strategic objectives and Nexus platform evolution.Lead architecture design across operational, analytical, reporting, regulatory, and AI use cases.Drive consistency across data acquisition, storage, transformation, governance, and consumption layers.Establish architecture guardrails balancing agility, scalability, maintainability, and regulatory compliance.Modern Data Platform ArchitectureServe as a senior technical architect responsible for end-to-end design of the Nexus ecosystem including:Data Ingestion LayerQlik Replicate and CDC patternsEvent-driven ingestion architecturesAPI-driven integrationsBatch and near real-time ingestion frameworksExternal and third-party data integrationData Storage & Processing LayersAWS S3 data lake architectureLanding and ingestion zonesSnowflake data platform architectureRaw Data Vault implementationBusiness Data Vault designConsumption and semantic layersData sharing and data product architecturesTransformation & OrchestrationDBT architecture and modeling standardsELT pipeline designReusable transformation frameworksAstronomer (Airflow) orchestration patternsWorkflow dependency managementData observability and monitoringOperational AnalyticsAPI-enabled data productsFargate-based servicesNear real-time analytics solutionsEvent streaming architecturesOperational reporting architecturesEnterprise Data Modeling LeadershipProvide deep expertise across multiple modeling disciplines:OLTP ModelingThird Normal Form (3NF)Operational application schemasTransaction processing systemsCustomer, account, loan, and transaction data structuresSource system integration patternsAnalytical Modeling (OLAP)Star schemasSnowflake schemasFact and dimension designAggregate layer strategiesSemantic modelingData Vault 2.0HubsLinksSatellitesBusiness Vault designPoint-in-time structuresBridge tablesAuditability and lineage patternsInformation ArchitectureEnterprise canonical modelsBusiness capability mappingCustomer 360 architecturesReference and master data designDomain-driven architectureArchitects in this role are expected to actively review and contribute to data models rather than simply approve designs.Data Products & Domain ArchitectureDrive adoption of data product thinking across ED&A.Define standards for ownership, accountability, quality, discoverability, and reuse.Partner with business domains to establish trusted and reusable analytical assets.Design scalable domain-oriented architectures supporting Data Mesh principles where appropriate.Enable self-service consumption through governed data products.Data Governance by DesignPartner closely with Governance teams to embed controls directly within architectural designs.Responsibilities include:Metadata architectureBusiness glossary alignmentTechnical and business lineageData quality architectureData contract implementationSensitive data classificationPolicy-based access controlData retention and auditabilityLeverage Collibra, BigID, and platform-native capabilities to improve trust and transparency across enterprise data assets.Performance Optimization & Engineering ExcellenceActively troubleshoot and improve platform performance by:Reviewing Snowflake query performanceOptimizing warehouse utilization and workload managementDesigning scalable partitioning and clustering strategiesImproving ELT processing efficiencyReducing data movement and duplicationEnhancing pipeline scalability and resiliencyEnsuring efficient storage and compute utilizationExpected to participate in technical deep-dives and solution reviews with engineering teams.AI & Advanced Analytics ArchitectureDefine architectural foundations for enterprise AI initiatives.Design AI-ready data products and curated consumption layers.Support feature engineering and model-serving architectures.Enable trusted, explainable, and governed AI data pipelines.Partner with Data Science teams to ensure scalability of predictive and generative AI solutions.Architect retrieval, metadata, and knowledge-layer capabilities supporting future GenAI initiatives.Technical LeadershipLead architecture reviews across strategic initiatives and programs.Influence technical direction across engineering, analytics, governance, and business teams.Mentor engineers, architects, and modelers on modern architecture principles.Establish engineering standards, design patterns, and reusable frameworks.Provide thought leadership on emerging technologies and industry best practices.Serve as the escalation point for complex architecture and modeling challenges.Bachelor's Degree and 6 years of experience in Enterprise data architecture, advanced data solutions, cloud platforms OR High School Diploma or GED and 10 years of experience in Enterprise data architecture, advanced data solutions, cloud platformsPreferred QualificationsFinancial Services or Banking industry experience.Experience modernizing legacy data warehouse environments.Experience architecting large-scale Customer 360 solutions.Experience supporting regulatory and risk reporting ecosystems.Knowledge of Data Mesh and Data Product operating models.TOGAF, CDMP, SnowPro, AWS, or equivalent certifications.Experience12+ years of experience in Data Engineering, Data Architecture, Information Management, or Analytics Engineering.5+ years serving as a lead architect for enterprise-scale data platforms.Proven experience designing and implementing modern cloud data platforms.Demonstrated experience leading large-scale data modernization programs.Experience working directly with