Senior Data Architect

Description

Job Summary: We are seeking a professional to implement and operate MLOps, design robust data solutions within the Microsoft ecosystem, and define enterprise data governance. Key Highlights: 1. Technical expertise in MLOps and data solutions. 2. Opportunity to define architecture and standardize development practices. 3. Involvement in designing and operationalizing data governance. Description: What we expect from you for this role: * Education: Bachelor’s degree or higher in Computer Science, Information Systems, Software Engineering, Data Engineering, or related field. * Proven experience with Microsoft data platforms (Azure) and their ecosystem for data ingestion, processing, storage, analysis, and orchestration. * Experience with MLOps in the Microsoft ecosystem, including versioning, environment promotion, model monitoring, and production operations. * Prior experience with DevSecOps/DataSecOps applied to data and models, focusing on automation, versioning, and continuous integration. * Experience defining and implementing enterprise data governance based on industry frameworks (e.g., DAMA\-DMBOK), covering policies, standards, roles, processes, and metrics. * Advanced knowledge of metadata management, data lineage, data glossary/dictionary, data quality, and operational governance models in an enterprise context. Preferred Qualifications: * Practical experience with Azure Databricks applied to Data Science projects already deployed in production within the Microsoft environment. * Microsoft certifications in the data and/or analytics track. In this team, you will have the opportunity to: * Implement and operate MLOps (model lifecycle, monitoring, traceability, and governance), ensuring quality and reliability in production. * Publish applications and pipelines following best practices, structuring environments (DEV/QA/PRD), release criteria, and rollback tracks. * Serve as a technical reference, leading alignment sessions, code reviews, mentoring, and workshops to elevate the technical maturity of teams. * Design, develop, and implement robust, scalable, and secure data solutions within the Microsoft ecosystem, covering architecture, integration, processing, storage, and analysis. * Define target architecture (Data Lake / Lakehouse) and standardize development practices (versioning, code review, testing, environment promotion). * Define and assist in implementing an enterprise data governance model aligned with industry frameworks (e.g., DAMA\-DMBOK), including roles and responsibilities (data owner/steward), governance councils, corporate policies, and standards. * Structure and operationalize data quality processes, corporate data glossary and dictionary, taxonomies, lineage, and metadata, as well as data indicators and SLAs/SLOs. * Model data (relational and dimensional), define flows and integrations, with emphasis on performance, scalability, and cost-efficiency. * Establish and disseminate data governance and security standards compliant with the Microsoft portfolio, covering access policies, compliance, and auditing. * Monitor system and pipeline performance, identify bottlenecks, and lead optimization and automation initiatives. * Evaluate and recommend approaches within the Microsoft portfolio, ensuring alignment with business needs and corporate architecture guidelines. * Document architectures, workflows, technical decisions, and best practices, keeping repositories and artifacts up to date. 2512300202491776925