Cleberson Amaral
Data Engineer @Dignity Plc
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WORK HISTORY
Data Engineer @Dignity Plc
Design and operate cross-platform data architecture across Azure (ADF, Azure SQL, Azure Data Lake) and modern data stack (Fivetran, BigQuery, dbt).Maintain and evolve both ETL and ELT pipelines, ensuring scalability, reliability, and interoperability between platforms.Built a Kimball-based data warehouse and established a robust semantic layer for enterprise analytics.Achievements:Led initiatives that reduced Azure costs by 30% through ETL optimizations, table compression, and Python automation; downsized Azure SQL Server, saving 25% without affecting latency; and optimized Blob Storage usage, achieving a 92% reduction in storage consumption.
EDUCATION
Federal University of Rio de Janeiro
Big Data
Academie Linguistique Internationale - Montreal - Canada
Advanced English
Training Center Caelum
Computer Programming
MongoDB University
Data Modeling/Warehousing and Database Administration
Faculty of Technology of Sao Paulo
Information of Technology, Databases - Business Intelligence
Ka Solution
Data Modeling/Warehousing and Database Administration
BFBiz | Business For Business
Data Modeling/Warehousing and Database Administration
Federal University of São Carlos
MsC, Computer Science - Incomplete, Data Warehouse - Databases - Big Data
SKILLS
ABOUT CLEBERSON AMARAL
Certified Databricks and Microsoft Azure Data Engineer with 13+ years of experience delivering scalable, enterprise-grade data and BI solutions. Design and operate cross-platform data architecture across Azure (ADF, Azure SQL, Blob) and modern data stack (Fivetran, BigQuery, dbt), maintaining both ETL and ELT pipelines with high reliability and scalability. Own the end-to-end data lifecycle, including ingestion, modelling (Kimball), governance, and performance optimisation, with experience building data warehouses and semantic layers from scratch. Modernise legacy platforms and drive adoption of modern data practices (ELT, modular modelling, decoupled architecture), enabling efficient integration and high-impact analytics.Proven track record in modernizing legacy systems, automating ETL/ELT pipelines, building data warehouses from scratch, integrating diverse data sources, and enabling analytics that drive business impact—achievements include 30% Azure cost reduction and creation of high-performing, cost-efficient data solutions.
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