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Meticulous Data Engineer with 5+ years' experience in data science and machine learning models. Expert in machine learning,large dataset management,optimization in data structures, data modeling and deployment of Machine Learning Operations (MLOps) . 2+ years of experience in data engineering, accomplished in compiling, transforming and analyzing complex information through data ingestion, pipeline automation, ETL development, and data governance and warehousing. Adept in building and maintaining data lakes, implementing data security and compliance measures. Demonstrated success in identifying relationships and building solutions to business problems.

Delivered scalable, high-performance data engineering solutions with over 11 years of IT expertise in Data Engineering, Data Warehousing, and Big Data. Leveraging 5+ years of experience in data engineering and 4+ years in data warehousing across healthcare, finance, retail, and manufacturing domains. Designed, built, and optimized large-scale ETL/ELT pipelines using Azure Data Factory, Azure Databricks, AWS Glue, Snowflake, and Apache Spark. Implemented real-time data ingestion and analytics pipelines leveraging Kafka, Spark Streaming, Azure Event Hubs, and AWS Kinesis. Developed reusable, parameterized pipelines to reduce development time and improve maintainability. Created optimized data models and schemas using dimensional modeling techniques (star schema, snowflake schema). Applied advanced performance tuning techniques such as partitioning, bucketing, indexing, caching, and workload management. Integrated structured, semi-structured, and unstructured data from diverse sources including RDBMS, APIs, and cloud storage. Automated ETL workflows using Apache Airflow, Oozie, Control-M, IBM Tivoli, Jenkins, and Azure DevOps pipelines. Utilized advanced Snowflake features including SnowSQL scripting, time travel, zero-copy cloning, and complex SQL functions. Built CI/CD frameworks for automated deployment, testing, and version control of data pipelines using Git, Jenkins, and Azure DevOps. Developed robust data quality and validation frameworks to ensure dataset integrity and reliability. Managed large, distributed clusters and fine-tuned Spark jobs for optimal performance and scalability. Designed real-time analytics dashboards with Power BI and Tableau for actionable business insights. Wrote complex SQL queries, stored procedures, triggers, and functions for data transformation and reporting. Processed geospatial and time-series datasets using specialized algorithms and frameworks. Created monitoring frameworks using AWS CloudWatch, Azure Monitor, and custom logging systems. Implemented data security and governance measures including RBAC, encryption, GDPR, and HIPAA compliance. Integrated hybrid data sources between on-premises and cloud environments. Mentored and guided junior data engineers, fostering collaborative learning. Collaborated with stakeholders to translate business requirements into scalable technical solutions. Operated effectively within Agile and Scrum frameworks (sprint planning, daily stand-ups, retrospectives). Delivered high-quality solutions on time while balancing technical and business priorities. Researched and adopted emerging data engineering tools and technologies. Transformed raw data into meaningful insights that drive business decisions. Change my professional summary for a business analyst position Senior engineering professional with deep expertise in data architecture, pipeline development, and big data technologies. Proven track record in optimizing data workflows, enhancing system efficiency, and driving business intelligence initiatives. Strong collaborator, adaptable to evolving project demands, with focus on delivering impactful results through teamwork and innovation. Skilled in SQL, Python, Spark, and cloud platforms, with strategic approach to data management and problem-solving.

 With over 15 years of expertise in Data Engineering and diverse Java technologies, an accomplished, self-motivated, and results-oriented cloud data engineer brings energy and proficiency in Big Data technologies, specializing in Python, Spark, Scala, Java, AWS, and Azure Cloud implementations. Substantial hands-on experience includes constructing scalable data infrastructure using Big Data platforms, navigating the Hadoop ecosystem, engaging in Java/J2EE web development frameworks, and handling various software engineering tasks. Skill set spans multiple niches. 

18 years of experience primarily in Banking and Financial Services, with strong expertise in FR 2052a FED Regulatory Reporting (5G & 6G), Analytics, and Data Governance. Proven track record in the design, development, and implementation of Cloud Data Lake, Data Mesh, Data Warehouse, and Business Intelligence solutions. Possesses strong technical, analytical, and functional skills, with end-to-end ownership across SDLC and Agile methodologies, including requirements analysis, documentation, architecture design, development, testing, implementation, production support, incident management, root cause analysis, and real-time debugging. Designed and delivered cloud-native solutions with a strong focus on engineering excellence, automation, innovation, and cross-team collaboration. Continuously evaluated and adopted new technologies, tools, and working practices, demonstrating agility and a strong learning mindset. Brought a curious, questioning approach to solution design, contributing innovative ideas and improving architectural and operational outcomes. Triaged complex production issues, performed root cause analysis (RCA), and made decisive, data-driven decisions under high-pressure scenarios. Acted confidently in break-glass production incidents, restoring services and minimizing customer impact during critical outages. Designed and implemented scalable solutions using AWS services, including compute, storage, networking, containers, and serverless frameworks. Built and deployed applications using Infrastructure as Code (IaC) tools such as Cloud Formation, Terraform, Ansible, and ARM, ensuring repeatability and compliance. Applied object-oriented principles and design patterns to develop maintainable, extensible, and high-performing applications. Developed and deployed containerized applications, leveraging Docker and Kubernetes, with strong experience deploying workloads on Amazon EKS. Implemented CI/CD pipelines using Jenkins and Git-based workflows, enabling automated build, test, and deployment processes. Collaborated effectively with distributed teams and stakeholders, both in-person and virtually, building trusted and productive working relationships. Worked with enterprise database technologies including Oracle, PostgreSQL, and SQL Server to support transactional and analytical workloads. Defined and implemented cloud reliability, resiliency, and observability strategies, ensuring high availability and performance of Tier-3 critical systems. Established and enforced engineering standards and best practices, contributing to increased engineering maturity and operational stability. Deployed and managed LLM-based solutions, including Retrieval Augmented Generation (RAG) architectures in cloud environments. Built full-stack AI-powered applications, integrating LLMs with backend services and cloud infrastructure. Applied best practices in prompt engineering, data privacy, hallucination mitigation, bias awareness, token usage, and cost optimization. Demonstrated understanding of GenAI modalities, determinism vs. randomness, and agentic behavior in production systems. Developed AI workflows and services using object-oriented Python, ensuring scalability, reliability, and maintainability. Data engineering professional poised to add significant value through comprehensive experience in developing scalable data solutions. Noted for strong team collaboration and adaptability in fast-paced environments. Reliable in driving results with key skills in data modeling, ETL processes, and cloud-based data platforms. Experienced with building and maintaining data pipelines to ensure seamless data flow. Utilizes advanced knowledge of big data technologies to drive data-driven decision-making. Track record of enhancing data architecture for improved performance and reliability. Senior engineering professional with deep expertise in data architecture, pipeline development, and big data technologies. Proven track record in optimizing data workflows, enhancing system efficiency, and driving business intelligence initiatives. Strong collaborator, adaptable to evolving project demands, with focus on delivering impactful results through teamwork and innovation. Skilled in SQL, Python, Spark, and cloud platforms, with strategic approach to data management and problem-solving. Diligent [Desired Position] with robust background in data engineering and proven ability to design and implement complex data pipelines. Successfully contributed to optimizing data architecture and enhancing data processing efficiencies. Demonstrated expertise in big data technologies and proficiency in Python and SQL. Responsive expert experienced in monitoring database performance, troubleshooting issues and optimizing database environment. Possesses strong analytical skills, excellent problem-solving abilities, and deep understanding of database technologies and systems. Equally confident working independently and collaboratively as needed and utilizing excellent communication skills. Detail-oriented [Job Title] designs, develops and maintains highly scalable, secure and reliable data structures. Accustomed to working closely with system architects, software architects and design analysts to understand business or industry requirements to develop comprehensive data models. Proficient at developing database architectural strategies at the modeling, design and implementation stages. Astute [Job Title] with data-driven and technology-focused approach. Communicates clearly with stakeholders and builds consensus around well-founded models. Talented in writing applications and reformulating models.

Thiago Porfírio

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Senior Data Engineer

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Senior Data Engineer

Data Engineer

Bachelor - Computer Engineering

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