<p>A global SaaS organization with a 30+ year track record and over 250 employees worldwide is seeking a <strong>Senior Data Architect</strong> to lead the design, implementation, and evolution of enterprise-grade data systems. The company operates across North America, Latin America, and additional international markets, with a focus on delivering scalable technology solutions to clients worldwide.</p><p><strong>About the Role</strong></p><p> This is a new and highly impactful position within the engineering function. The Senior Data Architect will be responsible for building and optimizing modern cloud-based data platforms that enable advanced analytics, AI integration, and operational intelligence. The role requires deep technical expertise, hands-on implementation skills, and the ability to guide global teams through complex data challenges.</p><p><strong>Key Responsibilities</strong></p><p><em>Architecture & Design</em></p><ul><li>Architect unified data models supporting modular and microservices-based systems.</li><li>Design and implement data lakes, data warehouses, and streaming/batch ETL pipelines.</li><li>Define and enforce data governance, metadata management, and observability standards.</li><li>Develop ontology frameworks and semantic data models for interoperability and intelligent querying.</li><li>Integrate structured and unstructured data into semantic layers for AI, vector databases, and knowledge graph applications.</li></ul><p><em>Hands-On Implementation</em></p><ul><li>Build and optimize ETL/ELT pipelines using Spark, Python, and SQL.</li><li>Implement data lineage tracking, schema evolution, and quality monitoring with modern tools.</li><li>Develop real-time telemetry pipelines feeding analytics and AI-driven workflows.</li><li>Configure and manage cloud-native data infrastructure and orchestration frameworks.</li><li>Prototype and deploy agentic AI workflows with semantic data integration.</li></ul><p><em>Collaboration & Leadership</em></p><ul><li>Partner with engineering, product, and AI teams to align architecture with business goals.</li><li>Mentor and upskill junior engineers, supporting global hiring and onboarding efforts.</li><li>Evaluate and integrate emerging technologies such as data mesh, data fabric, and semantic ecosystems.</li></ul><p><br></p>

<p><strong>Required Qualifications</strong></p><ul><li>10+ years of experience in enterprise data architecture and engineering.</li><li>Proven expertise in modern cloud data platforms (e.g., Azure Data Lake, Synapse, Databricks).</li><li>Strong proficiency in Python, Spark, SQL, and semantic modeling tools.</li><li>Experience with OWL, RDF, SPARQL, or equivalent semantic frameworks.</li><li>Deep understanding of data lineage, data catalogs, and knowledge graph development.</li><li>Track record of building scalable systems supporting analytics, AI, and operational workloads.</li></ul><p><strong>Preferred Skills</strong></p><ul><li>Certifications in cloud architecture (Azure, AWS, or equivalent).</li><li>Background in high-growth SaaS or transformation-stage enterprises.</li><li>Familiarity with data mesh, data fabric, controlled vocabularies, and linked data ecosystems.</li><li>Experience with AI integration, agentic frameworks, vector databases, and semantic telemetry.</li><li>Exposure to regulated industries such as Healthcare, Pharma, or FoodTech.</li></ul><p><strong>Success Metrics</strong></p><ul><li>Reduction in support tickets and performance bottlenecks tied to data architecture.</li><li>Accelerated adoption of AI and analytics enabled by robust data infrastructure.</li><li>Seamless integration of semantic models across business domains.</li><li>Enterprise-wide adoption of ontology-driven data practices.</li></ul><p><br></p>

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