Data Architect, LeadThe Lead Data Architect is a senior member of the Data team responsible for designing, developing, and maintaining enterprise and system-level conceptual, logical, and physical data models using Data Vault methodology within a Data Mesh architecture. This role translates the organization's data product strategy into actionable architecture solutions, ensuring data models, standards, and domain-aligned data products are consistently delivered across the enterprise. The Lead Data Architect works closely with data domain owners, Data Engineers, Analytics teams, and business stakeholders to build and evolve scalable, well-governed data products on the organization's Databricks-based platform, leveraging a custom automation framework and modern lakehouse patterns to drive domain-oriented, self-serve data capabilities.Tasks and ResponsibilitiesLead the design and development of conceptual, logical, and physical data models using Data Vault methodology for the enterprise Databricks lakehouse platform, ensuring alignment with architectural standards and business requirementsArchitect and evolve domain-aligned data products within a Data Mesh framework, ensuring each data domain delivers discoverable, addressable, trustworthy, and self-describing data productsCollaborate with data domain owners, Data Engineering, Analytics, and Business Relationship Management (BRM) teams to translate business needs into robust, domain-oriented data architecture solutionsDefine and maintain data modeling standards, naming conventions, and design patterns that support Data Vault modeling, Data Mesh principles, and a consistent data product lifecycle across the enterpriseDesign and extend the organization's custom automation framework on Databricks, leveraging latest platform components (Unity Catalog, Delta Live Tables, Databricks Workflows, Databricks Asset Bundles) to accelerate data product deliveryDevelop and enforce a decision-making framework aligned with data domains and data products, enabling domain teams to make autonomous architecture decisions within guardrailsDrive the implementation of master data management (MDM), metadata management, and data governance initiatives, leveraging Unity Catalog and platform-native capabilities for federated governanceConduct data architecture reviews for projects and data products to ensure compliance with enterprise data standards, Data Mesh principles, policies, and security requirementsCollaborate with the CISO and data protection teams to ensure data classifications, data zoning, and security requirements are embedded into data product and platform designsCreate and maintain architecture documentation, including data product specifications, data flow diagrams, entity-relationship diagrams, data dictionaries, and domain boundary definitionsSupport the development of enterprise data governance processes and structures, including data quality frameworks, data contracts, and data product SLAsIdentify and resolve data architecture issues, including data redundancy, cross-domain integration challenges, and performance bottlenecks across the Databricks platformParticipate in strategic roadmap planning by providing technical assessments and architecture recommendations for data products and analytics initiativesEvaluate emerging Databricks features, partner integrations, and data management trends to recommend improvements to the platform and automation frameworkMentor and provide technical guidance to Data Engineers and junior team members on Data Vault modeling, Data Mesh practices, and platform best practicesFacilitate communication with Databricks and other technology partners for technical evaluation, proof-of-concept efforts, and troubleshootingBalance tactical project delivery with adherence to long-term data product strategy and enterprise architectural visionBe accountable and responsible for the accuracy and completeness of assigned work and resultsPrioritize and manage workload and communicate issues clearlyComplete other tasks as requiredTravel when requiredMinimum EducationBachelor's degree from an accredited institution in Computer Science, Information Systems, Data Management, or a related field, or equivalent industry experienceMinimum Experience8+ years of experience in Information Technology, with a majority of experience in Data Architecture or Data Engineering5+ years of experience designing, building, and implementing enterprise data platforms, preferably on Databricks or similar lakehouse platforms3+ years of hands-on experience with Data Vault modeling methodologyExperience applying Data Mesh principles, including domain-oriented data ownership and data product thinkingExperience building or contributing to automation frameworks for data platform operationsExperience leading data architecture efforts across multiple concurrent projects or workstreamsKnowledge, Skills, AbilitiesStrong experience using data architecture and modeling tools such as Archimate, ER/Studio, or ErwinStrong experience in Data Vault 2.0 methodology, including hubs, links, satellites, and point-in-time/bridge table patternsSolid understanding of Data Mesh architecture principles, including domain ownership, data as a product, self-serve data platform, and federated computational governanceStrong experience defining and delivering data products with clearly defined contracts, SLAs, and quality standardsStrong hands-on experience with the Databricks platform, including Unity Catalog, Delta Live Tables (DLT), Databricks Workflows, Delta Lake, Databricks Asset Bundles, and Databricks SQLExperience building or extending custom automation frameworks for data pipeline orchestration, deployment, and platform operations on DatabricksSolid experience in master data management (MDM), data governance, and metadata management practices, including federated governance using Unity CatalogStrong knowledge of Azure cloud services that complement Databricks, including Azure Data Factory, Azure Analysis Services, and Power BIStrong expertise in enterprise-level data modeling, including relational, dimensional, and NoSQL design patternsUnderstanding of metamodels, taxonomies, and ontologies, and the ability to apply structured modeling techniques to semi-structured and unstructured data sourcesExperience with decision-making frameworks that align architecture choices with data domain boundaries and data product ownershipFamiliarity with data science concepts, business intelligence, and data warehouse design and implementation techniquesExperience with distributed data management and analytics in cloud and hybrid environments, including microservices and event-based architecturesKnowledge of problem analysis, structured analysis and design, and programming techniques (Python, SQL, Spark)Ability to assess emerging Databricks features and partner ecosystem technologies and evaluate their applicability to business needsStrong business acumen with the ability to communicate effectively with data domain owners, business stakeholders, and technical staffExperience with innovation and ideation methods such as design thinkingBusiness domain understanding; experience with Operations, Finance, Sales, or Marketing is preferredStrong experience working in Agile/SCRUM, KANBAN, and ITSM teamsAbility to mentor and guide team members on Data Vault modeling, Data Mesh practices, and platform best practicesStrong written and verbal communication skillsStrong organizational skills, including the ability to manage multiple priorities and workstreamsProven work ethic with the utmost integritySelf-awareness, with a desire for constant self-improvement (goal-oriented)Ability to build positive partnerships and work collaboratively with cross-functional and cross-domain teamsPhysical Demands and Work EnvironmentThe physical demands and work environment described here are representative of those that must be met and/or encountered by an employee to successfully perform the essential functions of this job. Reasonable accommodations may be made to enable individuals with disabilities to perform the essential functions.
While performing the duties of this job, the employee is regularly required to use hands to finger, handle, or feel; reach with hands and arms; and communicate. The employee may be required to stand, walk, and sit. Specific vision abilities required by this job include the ability to view monitors, technical documents, and reference material. The noise level in the work environment is usually low to moderate.FlightSafety is an Equal Opportunity Employer/Vet/Disabled.
All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, or disability. Any offer of employment is contingent upon successful completion of required compliance reviews, including verification that the candidate is not prohibited from employment under U.S. economic sanctions programs administered by the U.S. Department of the Treasury's Office of Foreign Assets Control (OFAC).
This position may require access to export-controlled technology or services subject to the International Traffic in Arms Regulations (ITAR) and/or the Export Administration Regulations (EAR). Employment consideration and any offer of employment are contingent upon the applicant's ability to comply with these requirements, including qualifying as a "U.S. Person" under applicable regulations or otherwise eligible for export authorization within a timeframe consistent with business needs.