Manage corporate data architecture and establish standards for data integration and modeling. Collaborate with teams on data governance and support BI, analytics, and machine learning initiatives.
Responsibilities
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 for data architecture, ensuring consistency 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 manner with teams such as:
Data Governance (policies, catalog, quality, and compliance)
DataOps (pipelines, execution, and operations)
Ensure the architecture supports scalable operations and effective 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 data 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
Strong understanding 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
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