I help organizations transform raw data into reliable reporting, analytics, and decision-support systems. My background combines Data Engineering, Analytics Engineering, and Monitoring, Evaluation & Learning (MEL) analytics. I design end-to-end data workflows that collect, process, transform, and visualize data to support operational and strategic decision-making. I have experience building production-style data solutions including automated ETL/ELT pipelines, PostgreSQL data warehouses, workflow automation systems, KPI reporting frameworks, and Power BI dashboards. Technical Expertise • SQL (Advanced Queries, CTEs, Window Functions, Query Optimization) • PostgreSQL • Python (Pandas, NumPy) • Airflow • dbt • Docker • Power BI • Data Warehousing • ETL / ELT Pipelines • API Integrations • Workflow Automation (n8n) • KoboToolbox Data Systems Services I Provide ✓ Data Pipeline Development ✓ ETL / ELT Workflow Automation ✓ PostgreSQL Database Design ✓ SQL Development & Optimization ✓ Data Warehouse Design ✓ Power BI Dashboard Development ✓ Monitoring & Evaluation (MEL) Reporting Systems ✓ KoboToolbox Data Processing & Reporting ✓ Automated Data Collection & API Integration ✓ Business Intelligence Solutions Selected Project Experience • Food Security Intelligence Pipeline Designed and deployed an automated humanitarian intelligence platform that ingests KoboToolbox survey submissions, processes vulnerability indicators, stores structured data in PostgreSQL, and generates operational alerts and reporting outputs. • Youth Employment MEL Analytics System Built a monitoring and evaluation database system using PostgreSQL and SQL analytics to assess employment outcomes, measure program impact, compare treatment and control groups, and generate donor-reporting indicators. • Data Warehouse & Analytics Engineering Projects Developing modern ELT architectures using Airflow, dbt, Docker, PostgreSQL, and object storage to support scalable reporting and business intelligence workflows. I focus on building solutions that are accurate, maintainable, scalable, and aligned with real operational needs. Whether you need a reporting dashboard, automated data pipeline, SQL optimization, or a complete analytics platform, I can help transform your data into actionable insights.

Data Engineer with expertise in data modeling (DBT), ETL/ELT processes, and managing GCP infrastructure for data storage, processing, and analysis. Proficient in SQL and Python, with a proven ability to deliver efficient and scalable solutions. Known for quick learning, logical thinking, and thriving in collaborative environments to meet project deadlines. Adept at leading and coordinating teams with a problem- solving mindset. Detail-oriented and self-managed, ensuring high-quality execution of tasks. Passionate about tackling new challenges and driving data-driven decision-making.

💼 About Me I’m a Data Engineer & Data Analyst with 4 years of professional experience in designing scalable data pipelines, automating ETL workflows, and delivering data-driven business insights. My core expertise includes Python, SQL, Power BI, IBM DataStage, and Web Scraping, helping organizations turn raw data into actionable intelligence. I’m passionate about solving complex data problems , from extraction and transformation to analytics and visualization ,ensuring every dataset tells a meaningful story. -------------------- 🚀 What I Do -------------------- 🔹 Design, build, and maintain ETL pipelines using IBM DataStage for full and incremental data loads. 🔹 Integrate and transform data from PostgreSQL, SQL Server, APIs, and flat files. 🔹Develop data validation and quality checks to ensure accuracy and consistency. 🔹 Automate data workflows using Python (Pandas, NumPy, Requests, BeautifulSoup, Selenium). 🔹 Create interactive dashboards and business reports in Power BI. 🔹Perform data cleaning, analysis, and visualization for actionable insights. 🔹Build custom web scraping solutions for data collection and trend analysis. I focus on reliability, scalability, and automation ,making sure your data systems perform efficiently and consistently over time. ------------------------- 🧠 Technical Skills ------------------------- Languages: Python, SQL ETL Tools: IBM DataStage, SSIS, AWS, Azure Databases: PostgreSQL, SQL Server, MySQL Visualization: Power BI, Excel Dashboards Automation & Analytics: Pandas, NumPy, PySpark, APIs Web Scraping: BeautifulSoup, Selenium, Requests Version Control: Git, GitHub -------------------------- 📂 Notable Projects -------------------------- 🔹 Microfinance Bank Data Pipeline: Designed and implemented a complete ETL process using IBM DataStage, integrating client, loan, and transaction data into a centralized SQL Server database. 🔹Shopify Sales Data Automation: Developed Python-based scripts to clean, merge, and analyze sales data, then visualized KPIs in Power BI dashboards. 🔹E-commerce Web Scraping: Built Python scraping bots (BeautifulSoup + Selenium) to extract product and pricing data from multiple online sources. 🔹Data Quality & Validation Framework: Created automated SQL and DataStage-based validation scripts to ensure consistent and accurate ETL data processing. These projects strengthened my ability to manage end-to-end data processes — from collection to insight delivery while maintaining quality and performance at scale. ------------------------------- 🎯 What You Can Expect ------------------------------- 🔹 Scalable, well-documented, and optimized data solutions 🔹 Timely delivery with clear communication 🔹 High data accuracy and performance-focused results 🔹 A proactive, detail-oriented, and reliable collaboration If you’re looking for a reliable Data Engineer or Data Analyst who can design end-to-end pipelines, automate workflows, and deliver insightful analytics . let’s connect and discuss how I can bring value to your project. 🚀

Most businesses don't have a single stack. Their data lives across Microsoft, AWS, and dozens of SaaS tools. I build the systems that bring it all together. DATA PLATFORMS & ANALYTICS ✦ Snowflake + dbt platforms with tested marts, versioned models, and source freshness monitoring at every layer ✦ AWS-native ingestion using S3, Snowpipe, and IAM storage integrations built for security and scale ✦ Microsoft Fabric data platforms designed around governance, reliability, and long-term maintainability ✦ Azure-to-Fabric migrations with Medallion Architecture implemented end to end ✦ OneLake-connected Power BI reporting that delivers trusted metrics and fast decision-making ✦ SaaS data consolidation across HubSpot, Stripe, Zendesk, Mixpanel, and other business systems AI & KNOWLEDGE SYSTEMS ✦ Production RAG pipelines with structure-aware chunking, versioned embeddings, and retrieval optimization ✦ pgvector and HNSW indexing for scalable semantic search ✦ Citation enforcement, audit logging, and source traceability built into every response ✦ AI systems designed for reliability, transparency, and operational use—not demos INTEGRATIONS & AUTOMATION ✦ Microsoft Graph, SharePoint, Teams, and Power Platform integrations when data workflows extend beyond analytics ✦ Automated data movement, validation, monitoring, and exception handling across cloud platforms RECENT OUTCOMES ✦ Delivered a Snowflake + dbt platform on AWS with 60+ tested models and sub-two-minute ingestion latency ✦ Unified HubSpot, Stripe, Zendesk, and operational data into a single reporting layer, eliminating weekly spreadsheet reconciliation ✦ Rebuilt a production RAG platform with citation enforcement and relevance controls, eliminating out-of-corpus responses in testing ✦ Reduced pipeline runtime by 30% during an Azure-to-Fabric Medallion Architecture migration completed within 8 weeks I work with 1–2 clients at a time because data platforms require ownership, not ticket-taking. Send me your current stack, architecture, or reporting challenges and I'll tell you honestly whether I'm the right fit.

I’m a Senior Data Engineer with strong experience designing and managing end-to-end data platforms, from raw ingestion to analytics and ML model deployment. My background spans both enterprise-scale systems and mentorship roles, where I’ve taught and implemented best practices in Python, SQL, dbt, Databricks, and PyTorch. Whether you need a robust ETL pipeline, a data lakehouse architecture on Databricks, or a dbt transformation workflow to power your dashboards, I can help you deliver clean, reliable, and scalable data systems. Core skills: * Databricks, PySpark, AWS Redshift, S3, and IAM * dbt Core & Cloud (CI/CD integration, testing, source freshness) * Data architecture and modeling (dimensional, star schema, ELT design) * Python, SQL, PyTorch, and machine learning integration * Workflow orchestration (Airflow, Databricks Jobs, dbt Cloud jobs) * Performance tuning and cost optimization on cloud data stacks

I’m a Senior Data Engineer specializing in Azure, AWS, Databricks, ADF, Snowflake, dbt, Python, and SQL. I build reliable, scalable ETL/ELT pipelines that turn raw data into clean, analytics-ready datasets. What I Do ETL/ELT pipeline development Modelling and Training pipelines Databricks & PySpark transformations ADF orchestration & automation Snowflake + dbt modeling Delta Lake (Bronze/Silver/Gold) SQL data validation & performance tuning Why Work With Me Senior-level problem solving Clear communication Clean, modular, production-ready code Tech Stack: Azure | Databricks | ADF | ADLS | Snowflake | dbt | Python | SQL | Linux

Results-driven Data & AI Engineer with proven expertise in designing and deploying scalable data platforms and AI-powered systems across cloud-native environments. Skilled in building end-to-end batch and real-time data pipelines using Python, SQL, Apache Spark, Kafka, Airflow, Snowflake, and DBT, with deep experience in AWS-based infrastructure and distributed data processing. Demonstrated success in integrating machine learning and LLM-driven solutions into production systems, including RAG-based pipelines, intelligent document processing, and predictive modeling frameworks that improved model performance by up to 20% and reduced processing time by 60%. Strong background in data modeling, ETL/ELT optimization, and data quality frameworks, enabling reliable and high-performance analytics systems. Experienced in developing data-driven products, including recommendation engines, financial analytics pipelines, and AI-powered feature extraction systems. Adept at applying MLOps, CI/CD, Docker, and Terraform to deliver production-ready solutions. Combines strong analytical thinking with business understanding to transform complex data into actionable insights that drive measurable impact.

I'm an architect and project manager turned data professional — which means I bring something most analysts don't: I understand the business behind the numbers, not just the numbers themselves. My focus is on helping companies in construction, real estate, infrastructure, and smart buildings turn raw data into decisions. That means clean SQL models, well-structured dbt projects, and dashboards that actually get used — not just built. My stack: SQL, Python, dbt Core, BigQuery, Looker Studio, GCP. I recently completed the DataTalks.Club Data Engineering Zoomcamp, where I built a production-grade ELT pipeline on London Smart Meters data — covering ingestion, transformation, orchestration, and visualization end to end. What I bring to analytics work specifically: domain knowledge that lets me ask the right questions before writing a single query, and engineering discipline that keeps models maintainable and results reproducible. Available for: exploratory data analysis, dbt modeling and documentation, dashboard development in Looker Studio, data pipeline support, and ad hoc reporting for construction and real estate clients. I also take on data engineering work — pipeline development, cloud infrastructure on GCP, and ELT architecture — for clients who need a solid data foundation before building analytics on top.

The two-second version: I am an analytics engineer with 3 years of hands-on practical experience in a fast-paced SaaS company. I have created various end-to-end data model pipelines and transformed raw data into strategic insights in a scalable approach for marketing, sales, product, and finance teams. I'd love to contribute my experience to your success. Excited to talk! ------ The longer, sit-down version: Pleasure to meet you! With a background in analytics engineering, I have designed and optimized scalable enterprise-level data model solutions that drive business growth. I developed a performance marketing model that enabled the team to measure ROI across multiple platforms. My cross-platform cost model saved $80K annually in FinOps tool subscriptions. My expertise spans SQL, DBT, BigQuery, and reporting tools. I thrive at the intersection of data, business, and technology, transforming raw data into actionable insights that fuel smarter decision-making. When you collaborate with me, you gain reliable, well-structured data models that empower informed decision-making. I ensure high-quality, efficient data pipelines, maintain data integrity, and create accessible insights tailored to your needs. I love working with data because it fuels my curiosity and passion for solving real-world business challenges. My goal is to foster long-term partnerships that drive impactful, sustainable results. Looking forward to optimizing your data landscape—reach out, and let’s build something exceptional together! Cheers, Yahui P.S. If your data challenges extend beyond what I’ve mentioned, feel free to connect! I’m always eager to explore new domains and deliver valuable solutions. Happy to be flexible as long as it aligns with our shared goals and adds value for both of us!

I design and build robust data pipelines that turn raw data into clean, actionable insights. I specialize in automating ETL workflows, integrating multiple data sources, and ensuring systems are reliable and scalable. My focus is on practical, well-engineered solutions that work in real-world scenarios and grow with your business. How I work: Analytical and quality-focused: I create systems that minimize errors and require minimal maintenance. Transparent communication: You’ll always know the status of your project, and I provide feedback quickly. Honest guidance: If a requirement doesn’t make sense, I’ll point it out and suggest better alternatives. Core skills: Python & SQL: Efficient, maintainable, and clean code. ETL/ELT & Data Pipelines: Python, DBT, Dagster, Databricks (PySpark), Airbyte. Data Cleaning & Transformation: Turning messy data into reliable, analytics-ready formats. Cloud & DevOps: AWS (Lambda, Glue, Athena, S3, EC2, Batch, Step Functions), Docker, ECS, Bash scripting, CI/CD (GitHub Actions, CodePipeline), Terraform. I deliver solutions that are accurate, scalable, and tailored to your needs. My goal is simple: make your data work for you, not the other way around.