I am a former finance consultant and operations manager turned data engineer. I combine my technical expertise in data management with my business knowledge to help you access and leverage your data. I can help you in the various stages of your data life-cycle : - Ingestion : finding the right tools to automate data extraction, whether from a local database, a cloud provider or a file system (Python, Airbyte, Fivetran). - Transformation : building and orchestrating the ETL/ELT pipelines to clean and transform your data (DBT, dataform, Airflow). - Service to business users : helping you find the right BI tool to access your data for analytical purposes (Looker studio, streamlit, Metabase) - Analytics : helping you analyze your data to uncover trends and make more informed decisions (exploratory analyses using python, SQL or Excel and machine learning using scikit-learn)

Hi, I'm a Data & Analytics Engineer with 3+ years of experience helping businesses transform raw data into reliable datasets, dashboards, and actionable insights. I specialize in designing and building end-to-end data solutions, from data ingestion and transformation to analytics-ready reporting layers. My experience includes working with large datasets, optimizing SQL queries, developing scalable ETL/ELT pipelines, and implementing modern data architectures. My expertise includes: ✔ Databricks & PySpark ✔ SQL & Query Optimization ✔ dbt (Data Build Tool) ✔ Azure Data Factory (ADF) ✔ Azure Data Lake Storage (ADLS) ✔ Data Modeling & Analytics Engineering ✔ ETL/ELT Pipeline Development ✔ Data Validation & Quality Checks ✔ Power BI & Business Reporting Over the past 3+ years, I have worked on analytics and data engineering projects involving financial, travel, and business reporting data. I have built data pipelines, implemented transformation frameworks, optimized data processing workloads, and delivered trusted datasets for reporting and decision-making. What you can expect when working with me: • Clear and proactive communication • Reliable and maintainable solutions • Focus on data quality and accuracy • Timely delivery • Business-oriented approach to problem-solving Whether you need a data pipeline, data warehouse solution, Databricks implementation, dbt project, reporting dataset, or SQL optimization, I would be happy to discuss your requirements and help you achieve your goals. Let's connect and build something valuable together.

🔍 Expert Data Scientist and Analytics Engineer With extensive experience in data science, analytics, and engineering, I am your go-to expert for turning complex data into actionable insights. As the current technical lead for a boutique consulting company, I have successfully led projects for a diverse range of clients, from large organizations like KPMG and Hagerty Consulting to public sector entities such as New York City Emergency Management. Key Skills and Expertise: Programming: Python, SQL, R Data Visualization: Tableau, PowerBI, Looker, Matplotlib, ggplot Data Engineering: Building robust data pipelines, ETL processes (dbt, BigQuery, Apache Spark, Hadoop) Machine Learning: Predictive modeling, NLP, sentiment analysis, algorithm development Analytics: Statistical analysis, A/B testing, KPI development, causal inference Technical Tools: Git, HTML/CSS, Power Automate, Tableau Site Administration, Agile (Jira), Process Flow Mapping What I Offer: Comprehensive Data Solutions: From data collection and cleaning to analysis and visualization, I provide end-to-end data solutions tailored to your needs. Actionable Insights: My work focuses on delivering clear, actionable insights that drive decision-making and improve business outcomes. Custom Dashboards and Reports: Using Tableau, PowerBI, or Looker I create intuitive and interactive dashboards that help you monitor key metrics and trends. Technical Leadership: With a proven track record of leading technical teams and projects, I ensure high-quality results delivered on time and within budget. Notable Projects: Cloud Data Warehouse Development: Developed a cloud-based database to manage over 2 million entries, increasing daily processing by 10x for all users. Technologies used: Python, REST APIs, Microsoft Azure SQL Database, Power Automate, Salesforce. Sentiment Analysis for UX Improvement: Implemented an NLP model for sentiment analysis and topic modeling, analyzing over 10,000 posts to extract actionable insights, identifying 80+ feedback points for website improvement. Technologies used: Python, NLTK, Vertex AI. Facebook Ads Optimization: Led Facebook Ads A/B testing initiatives, resulting in a 30% improvement in click-through rates and a 10% increase in conversions for clients. Technologies used: Looker, Google Analytics. I am passionate about leveraging data to solve real-world problems and am eager to bring my expertise to your next project. Let's work together to unlock the full potential of your data! Contact me today to discuss how I can help your business thrive.

I help businesses turn raw, messy data into clean, structured, and actionable insights. I specialize in building ETL/ELT pipelines and star-schema data warehouses using tools like Informatica PowerCenter, SSIS, dbt, and Apache Airflow, paired with interactive Power BI dashboards for reporting. Recent projects include: • An HR analytics pipeline consolidating data from multiple source systems into automated reporting • A retail data warehouse (Northwind) translating business requirements into measurable KPIs across sales, profitability, and logistics • A Python-based e-commerce ETL pipeline unifying data from multiple sources into a structured analytical model I'm currently deepening my expertise through an intensive Data Engineering training track, and I'm comfortable working across SQL Server, MySQL, PostgreSQL, and GCP BigQuery. If you need someone to design a data pipeline, build a data warehouse from scratch, or turn your spreadsheets into a live Power BI dashboard, I'd love to help.

Results-driven Senior AI Data Engineer with 5+ years of experience in Data Engineering, Analytics Engineering, AI-powered ETL development, and cloud-based enterprise data platforms. Strong expertise in Snowflake, SQL, Python, PySpark, Power BI, Tableau, Databricks, DBT, Matillion, AWS S3, Salesforce integrations, and modern analytics architectures. Specialized in building scalable data ecosystems, optimizing enterprise reporting platforms, and delivering analytics-driven business solutions that improve operational efficiency and decision-making. Strong analytical and problem-solving capabilities with hands-on experience in designing enterprise analytics platforms, developing KPI-driven dashboards, and generating actionable business insights from large-scale datasets. Expertise in data analysis, reporting optimization, data validation, reconciliation, and transforming raw enterprise data into meaningful analytical solutions for stakeholders and business teams. Extensive experience in Power BI and Tableau analytics development, including dashboard design, embedded analytics, data modeling, Power Query optimization, Row-Level Security (RLS), Entra ID authentication, and API-based secure dashboard integrations. Successfully delivered 100+ business dashboards and analytical reports providing real-time visibility into operational performance, customer analytics, financial metrics, and business growth indicators. Led Power BI to Tableau migration initiatives with improved dashboard usability, performance optimization, and enhanced end-user experience. Strong expertise in Snowflake architecture and analytics engineering, including warehouse optimization, query performance tuning, Time Travel, cloning, clustering, secure data sharing, cost optimization, and scalable data modeling. Designed and implemented enterprise data warehouse solutions capable of processing large-scale structured and semi-structured data efficiently. Experienced in dimensional modeling, star schema implementation, incremental loading, and CDC (Change Data Capture) frameworks to improve analytics performance and reporting efficiency. Hands-on experience in developing scalable ETL/ELT pipelines using PySpark, Matillion, DBT, SSIS, Celigo, and custom Python frameworks. Designed and delivered end-to-end enterprise data pipelines integrating multiple systems including Salesforce, Dialpad, Aircall, NetSuite, PostgreSQL, SQL Server, APIs, and cloud applications into Snowflake analytical environments. Skilled in building metadata-driven ETL frameworks, automated data synchronization systems, and optimized transformation pipelines for enterprise-scale analytics platforms. Experienced in AI-powered analytics and Generative AI implementations using Snowflake Cortex AI, Snowflake LLM functions, Cortex CLI, Claude AI, and Whisper AI. Built intelligent analytics solutions for customer call analysis, automated summarization, issue categorization, sentiment analysis, and AI-driven reporting. Strong knowledge of prompt engineering, prompt optimization, intelligent classification systems, and improving AI-generated analytical outputs for enterprise use cases. Worked as an LLM Trainer and AI solution contributor focused on improving AI accuracy, automation, and analytical insight generation. Strong hands-on experience in data processing, data cleansing, transformation, enrichment, aggregation, and quality assurance processes to ensure accurate and reliable reporting. Skilled in SQL query optimization, large-scale data analysis, debugging ETL workflows, troubleshooting production issues, and improving overall analytics system performance. Experienced in cloud-based data engineering and API-driven architectures using AWS S3, FastAPI, Fivetran, Databricks, REST APIs, and SnowSQL. Worked extensively with structured and semi-structured data formats including JSON and Avro for advanced analytics and enterprise reporting solutions. Demonstrated ability to build scalable, secure, and high-performance analytical ecosystems aligned with business requirements and modern cloud standards. Passionate about Analytics Engineering, Business Intelligence, Generative AI, intelligent automation, and modern cloud data platforms. Adept at collaborating with cross-functional teams, understanding business requirements, and delivering scalable analytics solutions that enable data-driven decision-making, operational excellence, and business growth.

I help companies turn data into business value. With a background in Physics and hands-on experience across Analytics, Data Engineering, and Data Architecture, I bring a unique combination of technical depth and business understanding. I don't just build dashboards, pipelines, or data platforms. I focus on solving business problems, improving decision-making, and maximizing ROI. Over the last few years, I have worked with modern data stacks including Snowflake, dbt, Airflow, AWS, Python, SQL, Tableau, and Redshift, delivering solutions that improve operational efficiency, reduce costs, and enable organizations to scale their data capabilities. My experience spans the entire data lifecycle: • Data Analytics & Business Intelligence • Data Engineering & Pipeline Development • Data Modeling & Data Warehousing • Data Architecture & Platform Design • Stakeholder Management & Business Translation What sets me apart is my ability to bridge the gap between technical teams and business stakeholders. I can discuss architecture decisions with engineers in the morning and help executives understand the business impact of those decisions in the afternoon. Whether you need to build a modern data platform, optimize existing processes, create actionable dashboards, or design a scalable analytics architecture, my goal is always the same: deliver measurable business outcomes, not just technical solutions.

I specialize in building scalable data infrastructures that empower businesses to harness their data effectively. With 11 years of experience as a Data and Analytics Engineer, I create robust data models using Star Schema, Snowflake Schema, and Data Vault modeling to meet diverse reporting needs. My technical expertise enables me to design systems that not only support current data requirements but also adapt to future growth.

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.

👋 Hi! I’m a Python Data Engineer & Data Visualization Expert at GroupBWT - a 100+ person data engineering company and official AWS, Snowflake & Databricks partner, building enterprise data systems since 2009. I architect scalable ETL/ELT pipelines and transform complex, multi-source data into reliable, executive-ready dashboards. Here’s how we support our clients: ✅ Our ETL pipelines process over 100 million records monthly across major cloud data warehouses ✅ My solutions reduce manual reporting effort by up to 80% through end-to-end automation ✅ We build Python-powered workflows for integrating, cleaning, and modeling complex datasets ✅ Every pipeline is tested and quality-checked to meet enterprise data standards 🔁 What I Do ⚙️Data Engineering 🔹API & event-based ingestion 🔹Python + SQL transformations 🔹Data modeling, schema design, enrichment 🔹ETL/ELT into Snowflake, Databricks, BigQuery 🔹Monitoring, retries, observability & data quality testing 🔹CI/CD for pipelines & cost optimization in cloud Platforms I’ve delivered process 100M+ records/month, integrate 30-80+ APIs, and power real-time BI environments. 📊 Data Visualization & BI 🔹I bridge raw data with business decisions 🔹Power BI, Looker Studio & Tableau dashboards 🔹Executive KPI reporting 🔹Semantic layer & metric standardization 🔹Real-time reporting (<5 min latency) 🔹BI performance optimization 🔹Data storytelling for leadership & operations My solutions reduce manual reporting effort by up to 70-80% and significantly improve forecasting accuracy. 🧩 Recent Experience 🔹Retail & eCommerce Data Warehousing Built ingestion + normalization pipelines for 120+ eCommerce sources, syncing ~500K SKUs/day into Snowflake / BigQuery. Implemented product matching, deduplication, schema standardization, and incremental updates to keep analytics tables stable for BI. 🔹FinTech Ingestion & Reporting Layer Delivered an automated pipeline that pulls data from 30+ external/internal sources (APIs, DBs, files), applies validation rules and transformations, and loads curated datasets for financial reporting and near-real-time dashboards. Focus on accuracy, auditability, and consistent metric definitions. 🔹Government ETL & Document Processing Automated processing of 10K+ documents/day (PDFs + structured files): extraction, classification, field mapping, and loading into a unified database. Added monitoring, error handling, and QA checks so ops teams don’t manually reconcile data. 🔹Healthcare Data Normalization & Compliance Cleaned and standardized millions of records across fragmented healthcare datasets: schema mapping, PII-aware handling, validation, and reproducible transformations. Produced “analytics-ready” layers with clear lineage and quality controls for compliance-driven reporting. 🔹Large-scale Cloud Migrations Migrated legacy reporting from MSSQL + Excel into BigQuery/Snowflake: rebuilt data models, implemented incremental loads, replaced spreadsheet-based workflows with automated pipelines, and delivered dashboards that refresh on schedule. 💻 Tech Stack ⚙️Languages: Python, SQL, DAX, Power Query, PySpark, Scala, Bash/Shell, JavaScript, etc. ⚙️Data Engineering & Processing: PySpark, dbt, Airflow, Prefect, CDC, REST & GraphQL, etc. ⚙️Data Warehouses & Databases: Snowflake, Databricks, BigQuery, AWS, PostgreSQL, MSSQL ⚙️Cloud Platforms: AWS: S3, Glue, Lambda, CloudWatch, Athena, Redshift, BigQuery, Dataflow ⚙️Data Modeling & Architecture: Star schema, Snowflake schema, Lakehouse architecture, etc. ⚙️Monitoring & Data Quality: dbt, Prometheus, Grafana, AWS CloudWatch, GCP Monitoring, etc. ⚙️BI & Visualization: Power BI (Desktop, Service), Tableau, Looker Studio, Metabase, etc. ⚙️DevOps & CI/CD: Git, GitHub, GitLab CI, Docker, Terraform, etc. 🚀 If you need automated pipelines, clean data models, and executive-level dashboards - let’s connect. ➡️ Invite me to your job and let’s design a robust data strategy with a Data Engineer leading the way.

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.