Define, evolve and sustain the corporate data architecture, ensuring scalability, standardization and alignment with business and technology strategies
Establish and maintain architectural standards for:
data ingestion and integration
data modeling (layers, domains and contracts)
data consumption (serving layer, APIs, BI, Analytics and AI)
Act as a technical reference in data architecture, ensuring coherence across initiatives and teams
Define the architecture for new data projects and products, supporting squads in technical decision-making
Conduct design reviews and validate end-to-end data solutions
Work in an integrated way with the teams of:
Data Governance (policies, catalog, quality and compliance)
DataOps (pipelines, execution and operation)
Ensure the architecture supports scalable operations and efficient governance
Structure the architecture to enable:
BI and self-service analytics
data science and machine learning
AI and Generative AI (GenAI) initiatives
Define data standards for consumption by models, applications and digital products
Provide technical leadership to architects and/or data engineers
Influence technical decisions across multiple teams and areas
Define and evolve the data architecture roadmap
Requirements
Solid experience in large-scale data architecture
Mastery of concepts such as:
Data Lake, Data Warehouse and Lakehouse
data modeling (dimensional and/or domain-driven)
batch and streaming processing
Experience with cloud platforms (AWS, Azure or GCP)
Hands-on experience with:
Databricks and/or Spark
data ingestion, transformation and processing tools