Senior Data Architect

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FCamara Consulting & Training

WebsiteLinkedInAll Job Openings

1001 - 5000 employees

🏥 Healthcare

🛡️ Insurance

📦 Logistics

Healthcare • Insurance • Logistics

FCamara Consulting & Training is a Brazilian multinational firm specializing in digital transformation and consulting services. With over 17 years in the market, FCamara's ecosystem focuses on innovation, e-commerce, digital strategy, and the integration of technology solutions such as artificial intelligence and cybersecurity. The company collaborates with a variety of sectors including retail, healthcare, finance, and logistics, empowering more than 1,000 businesses to evolve in the digital realm.

📋 Description

• Design, implement and evolve modern data architectures (Lakehouse and Data Platforms). • Lead initiatives to modernize legacy data platforms to cloud environments (Azure, multi-cloud or hybrid). • Develop and maintain scalable and resilient data pipelines using ELT processes, batch, streaming and near real-time. • Implement and manage Bronze, Silver and Gold data layers. • Define and enforce data quality frameworks, including validation, monitoring, SLAs and quality controls. • Structure data governance processes, metadata management, data catalog, data lineage and data discovery. • Model data using approaches such as Data Vault, dimensional modeling and semantic layers for Analytics and AI. • Prepare data for Machine Learning and Artificial Intelligence initiatives, including feature engineering and data preparation. • Optimize performance and costs of distributed workloads on data platforms. • Define architectural standards, data engineering best practices and technical guidelines for the team. • Implement best practices for versioning, automated testing, observability and pipeline monitoring. • Lead data platform transformation initiatives, promoting concepts such as Data Mesh, Data as a Product and AI-ready Data Platforms. • Work with technical and business areas to identify needs and turn data into strategic assets. • Ensure data security, governance and access control through security policies and RBAC.

🎯 Requirements

• Strong experience in Data Engineering and Data Architecture. • Advanced knowledge of Lakehouse architectures and modern data platforms. • Experience with distributed processing using Apache Spark. • Experience modernizing legacy environments to the cloud (preferably Azure; may include hybrid or multi-cloud). • Experience building and orchestrating ELT, batch and streaming pipelines. • Knowledge in data modeling (Data Vault, dimensional and semantic). • Experience with data quality frameworks, governance, data catalog, metadata and data lineage. • Knowledge of data integration for Analytics, Machine Learning and Artificial Intelligence projects. • Experience optimizing performance and costs in distributed environments. • Familiarity with modern software engineering practices, including version control, automated testing, observability and monitoring. • Knowledge of data security, access control (RBAC) and governance policies. • Technical leadership ability, setting standards and evolving data platform maturity. • Ability to work in multidisciplinary environments, connecting technical teams and business areas. • Experience with product-oriented data platforms (Data as a Product). • Experience implementing Data Mesh. • Knowledge of AI-ready Data Platforms. • Experience building datasets and semantic layers for AI and Analytics. • End-to-end view of the data journey, from ingestion to consumption by AI applications. • Strong focus on Data Quality as a pillar for AI model reliability. • Practical experience with modern governance and metadata management frameworks. • Experience in technical leadership of Data Engineering teams.

🏖️ Benefits

• Not specified