I'm a Data Engineer with experience building data pipelines, data warehouses, and analytics solutions for SaaS, eCommerce, fintech, and other data-driven businesses. I help companies turn raw data into reliable, actionable insights by designing and maintaining ETL/ELT pipelines, data models, and reporting systems. My focus is on building scalable, efficient, and reliable data platforms that support business growth and decision-making. Whether it's integrating data from multiple sources, improving data quality, automating workflows, or optimizing existing systems, I enjoy solving data challenges and delivering practical solutions that create real business value. What I Can Help You Build • ETL & ELT Pipelines • Data Warehouses & Lakehouses • Analytics & Reporting Platforms • Data Integration Solutions • Real-Time Data Processing Systems • Data Quality & Validation Frameworks • Monitoring & Alerting Infrastructure • Business Intelligence Data Models • API, Webhook & Third-Party Integrations • Cloud-Based Data Platforms Core Technologies Data Engineering: Python, SQL, PySpark, Airflow, dbt, Pandas Data Platforms: Snowflake, Databricks, PostgreSQL, Redshift, BigQuery Cloud & Infrastructure: AWS, Azure, Docker, Kubernetes, Terraform, CI/CD Analytics & BI: Tableau, Power BI, Looker My key strengths include building reliable ETL/ELT pipelines and designing scalable data warehouses that turn complex, messy data into structured, usable systems. I’m especially strong at finding and fixing root causes in broken data pipelines and making systems more stable, observable, and production-ready over time. If you need my help, let's discuss - I am open to consultation

Title: Analytics Engineer | dbt • SQL • BigQuery | Turning Raw Data into Insights Overview: Having refined my data skills within hyper-scale e-commerce and analytics environments like Amazon and leading enterprise platforms, I bridge the gap between data engineering and business intelligence. I help businesses transform messy SQL queries, broken dashboards, and untrusted data into clean, production-ready, and well-modeled data layers. As an Analytics Engineer, I apply software engineering best practices to data transformation. I don't just write scripts; I build version-controlled, tested, and documented data models using dbt and SQL, ensuring your business analysts and stakeholders always work with a single source of truth. 🛠️ What I Do Best: Data Transformation & Modeling: Designing clean, scalable Star/Snowflake schemas and dimensional data marts. Modern Data Stack (MDS) Implementation: Leveraging dbt (data build tool) to modularize, test, and automate your SQL pipelines. Data Quality Assurance: Implementing rigorous testing, data profiling, and documentation to eliminate "bad data" before it reaches your reports. Cloud Data Warehousing: Optimizing enterprise data warehouses (Google BigQuery) for peak query performance and cost efficiency. 💻 Technical Toolkit: Core: Advanced SQL (CTEs, Window Functions, Query Optimization), Python. Frameworks & Tools: dbt (Core/Cloud), Git/GitHub for version control. Cloud Infrastructure: Google Cloud Platform (BigQuery, GCS), Docker containerization. Big Data Ecosystem: Hands-on experience with Apache Spark for large-scale data ingestion and processing. 🌟 Why Hire Me? I treat data like software. Every model I build is optimized for cost, designed for speed, and documented so clearly that your internal team can manage it effortlessly moving forward. Let's clean up your data debt and unlock the true value of your data infrastructure. Click the "Invite to Job" button, and let’s discuss your project today!

👋 I'm a Data Scientist and Machine Learning Engineer with 8+ years of experience building end-to-end data systems, predictive models, and AI-powered applications that turn messy data into measurable business outcomes. 𝐌𝐲 𝐰𝐨𝐫𝐤 𝐬𝐢𝐭𝐬 𝐚𝐭 𝐭𝐡𝐞 𝐢𝐧𝐭𝐞𝐫𝐬𝐞𝐜𝐭𝐢𝐨𝐧 𝐨𝐟: data science, machine learning, data engineering, and applied AI systems (including LLMs and NLP). I don't just build models - I build complete data-to-decision pipelines: from data acquisition and cleaning, to modeling, deployment, automation, and visualization. 💪 𝐖𝐡𝐚𝐭 𝐈 𝐡𝐞𝐥𝐩 𝐜𝐨𝐦𝐩𝐚𝐧𝐢𝐞𝐬 𝐰𝐢𝐭𝐡 • Building predictive models for forecasting, classification, and decision support • Designing scalable data pipelines (ETL/ELT, automation, orchestration) • Extracting structured insights from unstructured data (text, web, APIs) • Web scraping and data collection systems at scale • BI dashboards and data visualization for business decision-making • LLM-powered applications (RAG, agents, summarization, classification) • Turning raw data into production-ready APIs and tools ⚙ 𝐂𝐨𝐫𝐞 𝐓𝐞𝐜𝐡𝐧𝐢𝐜𝐚𝐥 𝐒𝐭𝐚𝐜𝐤 • Machine Learning & Data Science PyTorch, TensorFlow, Scikit-learn, XGBoost, LightGBM, CatBoost, statsmodels • Data Engineering & Pipelines Python, SQL, PostgreSQL, MongoDB, Pandas, NumPy Airflow, dbt, ETL/ELT pipelines, data cleaning & transformation systems, Parquet, large-scale structured data processing • Web Scraping & Data Collection BeautifulSoup, Scrapy, Selenium, PRAW, APIs, FastAPI ingestion pipelines • NLP & LLM Systems OpenAI, Claude, Gemini, LLaMA, Mistral, DeepSeek HuggingFace Transformers, BERT, BART, SentenceTransformers, RAG pipelines, embeddings, vector search (FAISS, Pinecone, ChromaDB) • Visualization & BI Matplotlib, Seaborn, Plotly, Tableau, Power BI, Looker Studio, SHAP • Deployment & Cloud AWS (EC2, SageMaker, Bedrock), Docker, Firebase, VPS, FastAPI, Flask, WebSockets, Streamlit, Gradio 🎯 𝐖𝐡𝐨 𝐈 𝐰𝐨𝐫𝐤 𝐰𝐢𝐭𝐡 • Startups building AI-driven products and MVPs • Companies needing data pipelines, automation, or forecasting systems • Teams struggling with messy, unstructured, or incomplete data • Businesses wanting to turn raw data into actionable insights 🤝 𝐋𝐞𝐭'𝐬 𝐖𝐨𝐫𝐤 If you have a complex data or AI problem, I can help you: • define the right approach, • build a working system, • and deliver something production-ready. Send me a message - I typically respond within 24 hours with whether I can help and the best way to approach your problem.

I am a Data Analyst and BI Developer specializing in transforming complex datasets into actionable insights. With a background in Economics and experience at a government treasury department, I excel in developing analytical solutions that drive strategic decision-making. I created the New Oil Revenue Dashboard, a key Business Intelligence tool for monitoring oil revenues and resource allocation in Rio de Janeiro. My expertise includes SQL, Power BI, Python, and data modeling, enabling me to deliver reliable analytics solutions tailored to specific business needs. I am Microsoft DP-900 certified and eager to leverage my skills to help clients develop scalable data products and enhance their analytics capabilities. If you're looking for a detail-oriented analyst who can effectively translate data into impactful business strategies, I would love to discuss your project.

Your data is messy. Pipelines break. Reports take forever to load. I fix that. I build reliable ELT pipelines that take raw data from APIs, CSVs, or databases and turn it into clean, analytics-ready warehouses. What I bring: • End-to-end pipeline design from ingestion to analytics • Airflow workflows that run reliably on schedule • dbt models with tests, docs, and Bronze/Silver/Gold structure • BigQuery, PostgreSQL, and AWS S3 • Docker-based deployments for reproducibility Recent projects: → EarthquakeFlow: ELT pipeline ingesting USGS data into BigQuery with Airflow + dbt → OlistFlow: Data warehouse for 100K+ e-commerce records with staging, facts, and dimensions → AWS S3 Medallion Pipeline: Bronze → Silver → Gold architecture with Python + AWS I write clean, documented code and communicate clearly throughout the project. If you need data that moves, transforms, and actually works, I’d be glad to help.

I'm a Senior Data Engineer with 10+ years of experience designing, building, and optimizing scalable cloud data platforms for global enterprises. I specialize in developing high-performance ETL/ELT pipelines, modern data warehouses, and real-time streaming solutions across Google Cloud Platform (GCP), Microsoft Azure, and AWS. I help organizations modernize their data platforms, migrate legacy ETL systems to the cloud, optimize Spark and SQL workloads, and build reliable, analytics-ready data pipelines that improve performance while reducing operational costs. My expertise includes: ✔ ETL/ELT Pipeline Development (PySpark, Python, SQL) ✔ Cloud Data Engineering (GCP, Azure, AWS) ✔ BigQuery, Snowflake & Databricks ✔ Apache Spark & PySpark Optimization ✔ Azure Data Factory, Airflow & Cloud Dataflow ✔ Data Warehousing & Dimensional Modeling ✔ dbt, Lakehouse & Medallion Architecture ✔ Kafka & Pub/Sub Streaming Pipelines ✔ CI/CD, DataOps & Data Quality ✔ Cloud Migration & Platform Modernization What I can help you with: • Design scalable cloud data platforms • Build high-performance ETL/ELT pipelines • Migrate legacy ETL tools to modern cloud architectures • Optimize PySpark, SQL, and BigQuery performance • Develop real-time streaming data pipelines • Implement enterprise data warehouses • Reduce cloud costs and improve pipeline reliability I believe in writing clean, maintainable, and production-ready code while delivering solutions that are scalable, cost-effective, and aligned with business goals. I value clear communication, timely delivery, and long-term client relationships. Let's discuss how I can help build or modernize your data platform.

I am a Data Engineer and Business Intelligence professional with expertise in data warehousing, ETL development, and SQL optimization. I specialize in building robust data marts and scalable data pipelines using tools like Azure Data Factory, Snowflake, dbt, and SQL Server. My experience includes crafting Silver and Gold Architecture for analytics solutions that drive business performance. I deliver insightful Power BI reports that enable data-driven decision-making. With a solid understanding of data flow procedures and a proficient command of Microsoft 365 applications, I ensure seamless integration and operational efficiency. If you're looking for someone who can transform complex data into actionable insights, let's connect to discuss how I can help elevate your data projects.

As a Databricks Certified Data Engineer Associate with 4+ years of experience, I help businesses design, build, and optimize modern data platforms that turn raw data into actionable insights. I specialize in developing scalable ETL/ELT pipelines, cloud-based data lakes, lakehouse architectures, and real-time data processing solutions using Azure, AWS, Databricks, Spark, Python, and SQL. I have successfully delivered data engineering solutions for banking, fintech, and enterprise clients involving: ✔ Data Lake & Lakehouse Implementations ✔ Azure Databricks Development ✔ Apache Spark & PySpark Processing ✔ ETL/ELT Pipeline Development ✔ Azure Data Factory (ADF) ✔ AWS Glue, S3 & Redshift ✔ Delta Lake Optimization ✔ Apache Airflow Orchestration ✔ DBT Transformations ✔ CDC & Real-Time Streaming ✔ Data Warehousing Solutions ✔ Data Governance & Data Quality ✔ Denodo Data Virtualization What I Can Help You With Build end-to-end ETL/ELT pipelines Design scalable Lakehouse architectures Migrate legacy ETL systems to Databricks Implement Delta Lake best practices Develop real-time streaming pipelines Create cloud-native analytics platforms Optimize Spark performance and costs Build Data Warehouses and Data Marts Implement Data Governance frameworks Develop Airflow and DBT workflows Why Clients Work With Me ✅ Databricks Certified Data Engineer Associate ✅ Strong expertise in Azure & AWS ecosystems ✅ Banking and enterprise data engineering experience ✅ Performance optimization and cost reduction focus ✅ Clean, maintainable, production-grade solutions ✅ Strong communication and documentation skills If you're looking for a reliable Data Engineer to build scalable, high-performance data platforms, let's discuss your project.

I design, build, and manage scalable, reliable data platforms that transform raw data into meaningful business insights. As a Data Engineer, I specialize in modern data stack technologies including Snowflake, dbt, Databricks, Pentaho, and AWS services such as S3, Glue, MWAA, Athena, Step Functions, Redshift, and RDS. I help organizations streamline data workflows, improve data quality, and develop efficient data pipelines that support analytics, reporting, and business decision-making. What I deliver: End-to-end ETL/ELT pipeline development using Python, PySpark, SQL, and Pentaho Data integration and orchestration using Pentaho Data Integration (PDI) Data modeling and transformation with dbt for clean, analytics-ready datasets Scalable cloud-based data solutions on AWS Data warehouse design, migration, and optimization using Snowflake & Databricks Workflow orchestration with MWAA (Airflow) and AWS Step Functions Data governance, lineage, and quality management using Atlan Performance tuning and optimization of ETL workflows and SQL queries Analytics & Reporting: I also support downstream analytics by creating clean, business-ready datasets and interactive dashboards using Tableau, enabling clear reporting, KPI tracking, and data-driven insights. How I work: Write clean, maintainable, and scalable code using OOP principles Follow Agile & Scrum methodologies for efficient project delivery Apply Test-Driven Development (TDD) practices Use Git & GitHub for version control and collaboration Manage workflows and documentation using JIRA and Confluence I focus on delivering data solutions that are not only functional, but also scalable, cost-efficient, high-performing, and easy to maintain. Let’s build a modern data platform that grows with your business.

I help companies turn messy, unreliable data into clean, production-grade pipelines and trustworthy analytics on Google Cloud. Senior Data Engineer with 10 years of experience across data engineering, data science and business intelligence. I build and fix the GCP data stack that teams can actually rely on, from ingestion to BI-ready datasets. What I can do for you: - Build GCP data pipelines: BigQuery, Dataflow, Cloud Composer / Apache Airflow, dbt, Python, SQL - Rescue slow, fragile or undocumented pipelines (performance, reliability, data quality, monitoring) - Model clean, analytics-ready datasets for reporting and BI - Automate data workflows and infrastructure with Terraform (IaC) - Turn business questions into practical models: churn, customer lifetime value, segmentation Background: I have delivered data work for Atos (BI consulting), PagesJaunes (customer analytics: lifetime value and churn modeling) and Equancy (data engineering and data science). I bridge raw pipelines and real business decisions, not just moving data but making it useful. How I work: Reliable delivery, clear communication, clean and maintainable code. Fully remote, comfortable with both technical and business teams, in English or French. If your data stack is slow, messy or hard to trust, let's talk. I'll help you make it clean, reliable and ready to scale.