Principal Engineer, Domain Knowledge - 220771

Our companyAt Teradata, we believe that people thrive when empowered with better information. Teradata Autonomous Knowledge Platform activates enterprise intelligence by unifying data, knowledge and business context to achieve tangible outcomes. With Teradata, organizations can provide agents with full context for impact when it matters. Our solution lets businesses connect and scale on premises, in the cloud, or through a hybrid approach. Teradata delivers real business value with AI.What You’ll DoWe are seeking a Principal Engineer , Domian Knowledge, to define and build the next generation of enterprise-scale data discovery, inventory, and metadata management capabilities across many verticals, such as Finance, Healthcare, etc. This is a highly strategic and hands-on technical leadership role for an industry-recognized expert who has successfully designed and deployed large-scale data catalog platforms across complex enterprises.You will own the architecture, engineering, and evolution of systems that enable employees, analysts, data scientists, AI agents, and business users to discover, understand, trust, and govern data assets across the organization. Think of this role as building and operating the enterprise's "library index" or "parts catalog" for data, where every dataset, table, document, API, feature, metric, model, and knowledge asset can be found, understood, and evaluated for use.You will own the strategy and technical execution of Teradata's Enterprise Context Engine Domain Knowledge — developing enterprise-leading capabilities to extract, curate, and continuously evolve structured metadata and business context supported by Teradata’s industry knowledge models to serve as a governed layer powering both human analyst acceleration and AI agent grounding. This role combines deep product thinking with ecosystem and platform leadership, spanning the full lifecycle from knowledge acquisition and curation to runtime delivery and continuous improvement.The Context Engine integrates robust database and catalog connectivity, intelligent query parsing, and Teradata's decades of industry knowledge — particularly in highly regulated enterprises — into a curated, continuously improving context layer. Context Engine is a platform that converts enterprise data estates into governed, agent-ready knowledge. Built for organizations where AI reliability and auditability are non-negotiable, Context Engine enables companies to deploy AI workflows on the data they already own — without rebuilding their infrastructure, without retraining their models, and without waiting for generic AI synthesis to learn the business terminology that took their analysts years to master.The ideal candidate combines deep technical expertise in metadata management, distributed systems, data platforms, search and indexing technologies, governance, lineage, and data quality with a passion for creating exceptional discovery experiences at enterprise scale.Data Discovery & Inventory LeadershipDesign and build enterprise-wide data catalog and metadata platforms that continuously discover, inventory, classify, and organize data assets.Create systems that automatically scan and ingest metadata from databases, data lakes, warehouses, streaming platforms, APIs, BI tools, AI platforms, and SaaS applications.Drive the vision for making organizational data as discoverable as products in an e-commerce catalog or books in a modern library system.Establish a unified metadata strategy spanning structured, semi-structured, and unstructured data assets.Search, Indexing & RetrievalArchitect highly scalable metadata indexing and search systems supporting millions to billions of metadata entities.Design semantic search, keyword search, metadata search, faceted navigation, and relevance-ranking capabilities.Leverage graph technologies, vector search, embeddings, and knowledge representations to improve discoverability.Build intelligent recommendation systems that help users identify trusted and relevant data assets.Metadata & Knowledge EngineeringLead development of metadata models, business glossaries, taxonomies, ontologies, and enterprise information architectures.Establish standards for technical, business, operational, and governance metadata.Design lineage capture and metadata synchronization frameworks across heterogeneous ecosystems.Build metadata knowledge graphs connecting datasets, pipelines, dashboards, reports, AI models, metrics, owners, and business domains.Trust, Governance & Data QualityIntegrate data quality, stewardship, ownership, compliance, and governance indicators into catalog experiences.Create mechanisms for trust scoring, certification, usage analytics, freshness monitoring, and policy enforcement.Partner with governance, compliance, privacy, and security organizations to ensure catalog accuracy and regulatory alignment.Drive enterprise-wide adoption of metadata standards and governance practices.AI & Intelligent DiscoveryEnable AI-powered data discovery experiences using LLMs, semantic understanding, and agentic workflows.Design retrieval frameworks that allow AI agents to identify, evaluate, and consume trusted enterprise data assets.Create metadata enrichment systems leveraging machine learning and generative AI capabilities.Develop next-generation conversational discovery experiences for enterprise knowledge workers.Who You’ll Work WithServe as a principal architect and thought leader across multiple engineering and data platform organizations.Influence enterprise data strategy and long-term platform investments.Mentor senior engineers and architects.Drive architecture reviews, technical standards, and engineering excellence across the metadata ecosystem.What Makes You a Qualified CandidateRequired Qualifications12+ years of experience building large-scale data platforms, metadata systems, search platforms, or knowledge management technologies.5+ years leading architecture and implementation of enterprise data catalog, metadata management, or data discovery platforms.Proven track record designing systems that inventory and index thousands to millions of enterprise data assets.Deep experience with metadata ingestion, metadata modeling, lineage, governance, and data asset management.Strong software engineering background with demonstrated expertise in distributed systems and platform engineering.Experience building highly available, cloud-scale systems running in production environments.Expertise in at least one major cloud platform (Azure, AWS, or GCP).What You’ll BringData Catalog & Metadata PlatformsHands-on experience with technologies such as:Microsoft Purview, Fabric, Fabric IQCollibraAlationDataHubApache AtlasInformatica Enterprise Data CatalogAtlanOpenMetadataSearch & Discovery TechnologiesDeep expertise in:Elasticsearch / OpenSearchSolrLuceneVector databasesSemantic search architecturesEnterprise search platformsRelevance ranking systemsData PlatformsExperience across:DatabricksSnowflakeMicrosoft FabricAzure Data LakeDelta LakeHadoop ecosystemsKafka and streaming platformsModern data warehousesMetadata & Knowledge TechnologiesExperience with:Knowledge graphsGraph databasesSemantic technologiesOntologies and taxonomy designEntity resolutionData lineage frameworksMaster data managementAI & Machine LearningExperience applying:Large language modelsRAG architecturesAgentic workflowsMetadata enrichment using AISemantic retrieval systemsAI-powered recommendationsWhat Distinguished Candidates DemonstrateRecognized leadership in the metadata, catalog, search, or knowledge management domains.Experience building enterprise-wide data discovery platforms adopted by tens of thousands of users.Proven experience delivering knowledge management systems in on-prem, regulated, sovereign and air-gapped environmentsDemonstrated ability to scale metadata systems across large, globally distributed organizations.Strong product thinking around discoverability, trust, usability, and developer experience.Ability to bridge data engineering, governance, AI, and business stakeholder communities.History of driving transformational initiatives from concept through broad enterprise adoption.Success MetricsWithin the first 12-18 months, this leader will:Deliver a unified enterprise inventory of critical data assets.Improve discoverability and reuse of trusted datasets across business domains.Increase metadata completeness, ownership coverage, and lineage visibility.Enable AI-assisted data discovery and self-service analytics experiences.Reduce time-to-find and time-to-trust for enterprise data assets.Establish a scalable metadata foundation powering governance, analytics, and AI across the organization.Why We Think You'll Love Teradata We prioritize a people-first culture because we know our people are at the very heart of our success. We embrace a flexible work model because we trust our people to make decisions about how, when, and where they work. We focus on well-being because we care about our people and their ability to thrive both personally and professionally. We are committed to actively working to foster an inclusive environment that celebrates people for all of who they are#LI-CP2 Teradata is proud to be an equal opportunity employer. We do not discriminate based upon race, color, ancestry, religion, creed, sex (including pregnancy, childbirth, breastfeeding, or related conditions), national origin, sexual orientation, age, citizenship, marital status, disability, medical condition, genetic information, gender identity or expression, military and veteran status, or any other legally protected status. We welcome and encourage individuals from all backgrounds to apply and join our team, bringing their unique perspectives and experiences to help us innovate and grow. If you require accommodations during the interview process, please let your recruiter know and we will work with you to meet your needs.