Hi! I can help your business solve problems with data, from the extraction of the data until mining, analyzing, and creating machine learning models. I have experience working with ETL projects for getting data to be used at the company software, resulting in a model for detecting plagues in sugarcane plantations at 95% accuracy. I also created projects from courses and by personal initiative, targeting improvements in my abilities for data science and machine learning problems, like a project for recommending recently published videos from YouTube based on people's personal tastes at searching for videos. Since I have this experience, we can create solutions using tools like AWS, SQL, Python, scikit-learn, and many other technologies, always trying to extract the best of them and getting better results. If you are interested, let's get it! Send me a message and tell me about your project. I'll be glad to help you!

I help businesses build scalable, high-performance data solutions. As a Senior Data Engineer with expertise in SQL, dbt, Snowflake, and data modeling, I specialize in designing, optimizing, and migrating data systems that drive business insights and efficiency. What I Offer: 🔹 End-to-End Data Engineering – ETL/ELT pipeline development, data modeling, and warehousing 🔹 dbt & BigQuery/Snowflake Migrations – Seamless transitions to modern cloud platforms 🔹 Performance Optimization – Faster queries, cost-efficient storage, and scalable architecture 🔹 Automation & Workflow Optimization – Reduce manual effort, ensure data reliability I specialize in these modern data stack technologies: 🔹 Data Ingestion – Airbyte, Fivetran, Stitch, Domo, Informatica PowerCenter 🔹 Data Warehouses – BigQuery, Snowflake, PostgreSQL, Redshift 🔹 Transformation and Modeling – dbt Core/Cloud 🔹 Orchestration and Scheduling – Airflow 🔹 Visualization – Looker Studio, Power BI Certifications: ✔ dbt Certified Developer I’ve successfully led data migrations, optimized performance, and reduced costs for multiple clients across various industries. If you're looking for a data ninja to build, enhance, or migrate your data platform, let's talk!

Data Engineer specializing in Analytics Engineering and cloud data pipelines. I design and build end-to-end pipelines — from raw ingestion to BI-ready data models — across the modern data stack. My recent projects span three major cloud platforms: Snowflake, Google BigQuery, and Azure/Databricks, using tools like dbt, Spark, Delta Lake, and GitHub Actions. I follow best practices including Medallion Architecture, dimensional modeling (Star Schema), incremental processing, data quality testing, and CI/CD automation. Whether you need a clean data warehouse, a reliable ETL pipeline, or automated reporting infrastructure, I deliver production-quality work with proper documentation and testing.

Most dashboards are not a reporting tool problem. They are a data problem. Wrong sources, broken refresh cycles, no proper model underneath. The result is a dashboard nobody trusts or uses. I am a 𝐁𝐈 & 𝐀𝐧𝐚𝐥𝐲𝐭𝐢𝐜𝐬 𝐄𝐧𝐠𝐢𝐧𝐞𝐞𝐫 with 𝟒+ 𝐲𝐞𝐚𝐫𝐬 of experience building 𝐦𝐨𝐝𝐞𝐫𝐧 𝐝𝐚𝐭𝐚 𝐢𝐧𝐟𝐫𝐚𝐬𝐭𝐫𝐮𝐜𝐭𝐮𝐫𝐞 for SaaS companies, marketplaces, and high-growth startups. I specialize in end-to-end data stack delivery, including multi-source ingestion, data warehouse setup, dbt transformations, orchestration, and dashboards that teams actually use to run their businesses. I work with the modern data stack, including dlt, Fivetran, dbt, BigQuery, Snowflake, ClickHouse, Dagster, and Hex. I deliver systems that you fully own. No proprietary SaaS lock-in. No black-box pipelines. Everything is thoroughly documented and handed over to your team. 𝐂𝐥𝐢𝐞𝐧𝐭𝐬 𝐜𝐨𝐦𝐞 𝐭𝐨 𝐦𝐞 𝐰𝐡𝐞𝐧: • Reporting is still manual and eats hours every week • Dashboards exist but numbers never agree across teams • Data is scattered across CRM, ads, product, billing, and support with no unified view • Postgres schema changes silently break downstream reports • They need a clean, production-grade data stack built properly from scratch • They want AI-derived signals sentiment scoring, churn flags, health scores automated into their dashboards 𝐒𝐞𝐫𝐯𝐢𝐜𝐞𝐬 • End-to-end data stack delivery (Ingestion → Data Warehouse → Transformation → BI & Analytics) • Multi-source ETL/ELT pipeline development using dlt, Fivetran, and Airbyte • Data warehouse design and implementation with BigQuery, Snowflake, ClickHouse, and Redshift • dbt data modeling, including staging, intermediate, and mart layers with testing and documentation • Pipeline orchestration using Dagster (Cloud and self-hosted deployments on Kubernetes, GKE, and AKS) • Dashboard and reporting development in Hex, Metabase, Looker, Power BI, and Tableau • Analytics solutions including revenue analytics, customer segmentation, product analytics, cohort retention analysis, churn prediction, and sentiment analysis • Data quality monitoring, documentation, and stakeholder-ready reporting 𝐌𝐲 𝐓𝐨𝐨𝐥𝐛𝐨𝐱: 📊 𝐁𝐈 & 𝐃𝐚𝐬𝐡𝐛𝐨𝐚𝐫𝐝𝐬: Hex, Metabase, Power BI, Looker Studio, Superset, Tableau, Klipfolio 💽 𝐖𝐚𝐫𝐞𝐡𝐨𝐮𝐬𝐢𝐧𝐠 & 𝐌𝐨𝐝𝐞𝐥𝐢𝐧𝐠: BigQuery, Snowflake, Clickhouse, Supabase, dbt 📈 𝐋𝐚𝐧𝐠𝐮𝐚𝐠𝐞𝐬: SQL, Python (Pandas, LangChain), R 📎 𝐒𝐨𝐮𝐫𝐜𝐞𝐬: GA4, Segment, Stripe, HubSpot, Mixpanel, Posthog, Pylon 🔄 𝐀𝐮𝐭𝐨𝐦𝐚𝐭𝐢𝐨𝐧 & 𝐖𝐨𝐫𝐤𝐟𝐥𝐨𝐰: Airbyte, Zapier, Slack, Notion I deliver production-ready data pipelines with dbt models, testing, and documentation, not just connected dashboards. Every solution is built for accuracy, maintainability, and long-term ownership by your team. Before project completion, I validate metrics, review outputs with stakeholders, and ensure the data is trusted and understood. 𝙃𝙖𝙫𝙚 𝙖 𝙙𝙖𝙩𝙖 𝙤𝙧 𝙧𝙚𝙥𝙤𝙧𝙩𝙞𝙣𝙜 𝙘𝙝𝙖𝙡𝙡𝙚𝙣𝙜𝙚? Send a brief overview of your data sources and goals. 📩 Just drop a message. I’ll take it from there. Talk soon, Hadiqa. Your data’s new best friend.

Building production data infrastructure and AI systems for clients across the US, UK, and Middle East. Top Rated on Upwork with 100% Job Success. I help businesses turn messy data into reliable pipelines and transform AI ideas into working products. Whether you need a data warehouse that scales, an LLM powered assistant, or automated workflows that save hours of manual work, I build systems that actually run in production. Data Engineering: I design and build ETL and ELT pipelines using Python, dbt, Airflow, and AWS Glue. I work with data warehouses like BigQuery, Snowflake, and Redshift, and have consolidated complex architectures into clean, maintainable systems. One project involved reducing 132 AWS Lambda functions down to 10 streamlined pipelines. I handle data modeling, dimensional design, and build dashboards using Looker Studio and Power BI that teams actually use. AI and LLM Systems: I build practical AI solutions using OpenAI, Claude, and open source models. This includes RAG pipelines with LangChain and vector databases like Pinecone and ChromaDB, custom chatbots, document assistants, and multi agent systems. I also work with agentic AI and workflow automation using n8n and OpenAI Agents to help businesses automate repetitive tasks. What I Work With: Python, SQL, dbt, Airflow, Spark, BigQuery, Snowflake, Redshift, AWS, GCP, Azure, Docker, FastAPI, Django, LangChain, OpenAI API, n8n, Pinecone, ChromaDB, Looker Studio, Power BI How I Work: I communicate clearly, respond quickly, and focus on delivering working solutions. I have experience working async with international teams and managing projects independently. I document my work and write clean, production ready code. If you have a data or AI challenge, send me a message. I am happy to discuss how I can help.

⏰ Available 24/7 – Long-term & High-impact Projects Hi, I’m Nghi, a Senior Data Engineer and Data Architect with a strong backend foundation, now focused on building high-performance analytics platforms, explainable data pipelines, and production-grade cloud architectures. I help companies transform unreliable, slow, or opaque data systems into scalable, well-documented, and business-trustworthy platforms. 🧠 WHAT I SPECIALIZE IN 🏗️ Data Architecture & Platform Design - Designing modern lakehouse & warehouse architectures - dbt-first analytics engineering with testing, freshness & lineage - Event-driven and batch hybrid pipelines - Data quality frameworks & SLA monitoring - Customer-facing data explainability systems Tools: dbt, Dagster, Airflow, Spark, Kafka, Snowflake, BigQuery, Redshift, PostgreSQL, DuckDB, ClickHouse ⚡ Database Performance Engineering - If your queries are slow, costs are high, or dashboards lag, This is my zone - Query plan analysis & index strategies - Warehouse cost optimization (Snowflake, BigQuery, Redshift) - OLTP & OLAP performance tuning - High-concurrency workload design 🔄 Reverse ETL & Operational Analytics - Syncing analytics back to CRMs & internal tools - Building real-time metrics pipelines - Feature-store style transformations 🕷️ Enterprise-grade Web Data Extraction - I don’t just scrape pages, I build durable data acquisition systems: - Complex ASP.NET, JS-heavy, authenticated & paginated systems - Anti-bot bypassing & failure-recovery pipelines - Headless browser automation + async scraping - Real-estate, finance, campaign-finance & marketplace platforms ☁️ Cloud Infrastructure - AWS | Azure | GCP - EMR / Dataproc / Glue / Dataflow / Synapse / BigQuery / Redshift - Terraform-based deployments - Cost-aware architectures - Kubernetes + Dockerized data services 🧪 What You Get Working With Me ✔️ Production-ready pipelines ✔️ Clean, testable dbt models ✔️ Well-documented architecture diagrams ✔️ Transparent data logic for non-technical stakeholders ✔️ Systems that scale beyond MVP ✔️ Honest advice and not over-engineering 🏆 Ideal Projects 👍 Data warehouse migrations 👍 Broken pipelines that need debugging & stabilization 👍 Analytics platforms that lack trust or explainability 👍 Performance bottlenecks costing thousands per month 👍 Long-term data platform ownership ❣️ Why Clients Stay Long-Term 🍀Clear communication 🍀 Business-first thinking 🍀 No black-box systems 🍀 I build systems others can maintain 🇻🇳🇻🇳🇻🇳🇻🇳 If your data platform feels fragile, slow, or impossible to explain to customers, I can fix that. Let’s make your data system something you can confidently stand behind.

✅ 4x Microsoft Certified (PL-300, AI-900, DP-900, MS-900) | 100% Job Success | Top Rated From Wall Street analytics to AI-powered dashboards. I build BI systems that C-suite executives trust to make decisions. With an Economics degree, a Systems Engineering degree, and experience at Morgan Stanley and Moody's Analytics, I bring a rare combination: I understand both the financial logic behind the numbers and the engineering required to deliver them reliably at scale. I also led M&A analytics at Kareo (healthcare SaaS) and founded Ceteryx, a data intelligence consultancy. 𝗪𝗵𝗮𝘁 𝗜 𝗗𝗲𝗹𝗶𝘃𝗲𝗿 𝗣𝗼𝘄𝗲𝗿 𝗕𝗜 𝗗𝗮𝘀𝗵𝗯𝗼𝗮𝗿𝗱𝘀 & 𝗥𝗲𝗽𝗼𝗿𝘁𝗶𝗻𝗴: Executive KPI scorecards, financial reporting suites, operational dashboards, designed for CFOs, COOs, and board presentations. 𝗣𝗼𝘄𝗲𝗿 𝗣𝗹𝗮𝘁𝗳𝗼𝗿𝗺 𝗔𝘂𝘁𝗼𝗺𝗮𝘁𝗶𝗼𝗻: Power Apps for data capture + Power Automate for workflow automation + Power BI for live reporting, a fully integrated Microsoft stack. 𝗔𝗜-𝗘𝗻𝗵𝗮𝗻𝗰𝗲𝗱 𝗕𝗜 𝗦𝗼𝗹𝘂𝘁𝗶𝗼𝗻𝘀: I integrate OpenAI/Claude into Power Platform workflows, automated executive summaries, anomaly detection, and natural-language data queries. 𝗖𝗥𝗠/𝗘𝗥𝗣 𝗜𝗻𝘁𝗲𝗴𝗿𝗮𝘁𝗶𝗼𝗻𝘀: Salesforce, HubSpot, Dynamics 365, NetSuite, QuickBooks. I connect your operational systems to Power BI for a single source of truth. 𝗗𝗮𝘁𝗮 𝗘𝗻𝗴𝗶𝗻𝗲𝗲𝗿𝗶𝗻𝗴: ETL pipelines (Python, Airflow, dbt), data modeling, Snowflake/PostgreSQL/Azure optimization. 𝗣𝗿𝗼𝘃𝗲𝗻 𝗜𝗺𝗽𝗮𝗰𝘁 Reduced ETL runtime 70% for a NASDAQ SaaS firm → $30K/mo in compute savings Built real-time fraud detection pipeline (99.3% accuracy) with Python & Kafka Migrated 50+ on-prem SQL databases to AWS with zero downtime Delivered CFO-grade SaaS metrics dashboards (MRR, LTV, churn) for board presentations 𝗪𝗵𝘆 𝗠𝗲 Ex-Morgan Stanley & Moody's Analytics: I speak finance fluently 4x Microsoft Certified: PL-300, AI-900, DP-900, MS-900 Founder of Ceteryx: entrepreneurial mindset, ownership mentality Fluent in English, Spanish, Italian Fast starts: most clients see first results in < 7 days Free 30-minute consultation to scope your project ⭐ Client Reviews "Built a dynamic, CFO-grade dashboard from minimal specs. Hit every deadline." "Joined disjointed data I thought impossible and delivered CXO-ready insights." "Responsive, insightful, knows the ins and outs of MS Power Platforms and OpenAI integration." 📞 Send me your data challenge: I'll blueprint a solution in 24 hours, no strings attached.

As a former Head of Data for a high-growth dating app, I've driven data-informed decisions that directly contributed to company expansion. My hands-on experience spans roles including analyst, developer, data scientist, analytics engineer, and data architect, providing me with a comprehensive understanding of the entire data lifecycle. My mission is to empower decision-makers with rapid access to actionable insights through robust data infrastructure and clear visualisations. I specialise in: • Data Visualisation: Expert in Mixpanel, Amplitude, Tableau, and Sisense • Data Modelling & Infrastructure: Proficient with DBT, Redshift, and BigQuery • Programming: Advanced SQL, Python, and R Key areas of expertise: Product Data Analysis • Translating high-level questions into data-driven insights • Guiding teams in hypothesis formulation and prioritisation • Designing and analysing A/B tests for product optimisation Business Intelligence Development • Architecting scalable data infrastructures • Implementing efficient data models using DBT • Creating intuitive, actionable dashboards Software Development • Building efficient, testable Python and PHP code • Applying object-oriented design principles and patterns • Leveraging AWS for robust backend infrastructure Data Architecture • Designing future-proof data architectures aligned with business objectives • Constructing data lakes using cutting-edge big data technologies • Optimising data infrastructure on AWS With a blend of technical prowess and business acumen, I deliver data solutions that drive growth, enhance decision-making, and unlock business potential. Let's collaborate to turn your data into a strategic asset.

As a seasoned data engineer, I have an impressive track record of delivering impactful solutions that drive data-driven decision-making. With expertise in architecting data warehouses, I have successfully designed and implemented robust systems from source system to modeling and BI layers. I have a keen eye for developing executive-level dashboards, enabling the presentation of key performance indicators (KPIs) to stakeholders for informed decision-making. My collaborative nature shines through as I work closely with cross-functional teams to gather requirements and transform them into technical solutions. I have led initiatives, such as sessionizing website event data for revenue attribution, showcasing my ability to drive innovative projects with tangible business outcomes. Mentoring junior developers is a passion of mine, and I take pride in providing guidance and expertise in code reviews, project direction, and meeting preparation, resulting in enhanced collaboration and improved code quality. Utilizing cutting-edge tools like dbt, Python (Airflow or Dagster), and Snowflake, I have developed and modeled data into consumable formats, including staging, base, intermediate, dimension, and fact tables. I have extensive experience with complex SQL queries and have leveraged my knowledge of data modeling methodologies like Data Vault. Additionally, I have successfully migrated on-premise data to the cloud using Microsoft Azure and Databricks, showcasing my ability to leverage advanced technologies for seamless data platform migration. My ability to collaborate closely with stakeholders, including C-level executives, has led to valuable insights and the development of comprehensive Power BI dashboards across various business functions. I have also demonstrated my analytical acumen by developing risk models using Bayes Theorem, enabling proactive risk mitigation and informed decision-making. Leveraging the power of Databricks, I have designed and implemented robust data pipelines, ensuring efficient data transformation and processing. With a strong track record in data engineering and a wide range of technical skills, I am well-equipped to drive data initiatives and deliver impactful solutions in any data engineering role.

I translate complex data challenges into scalable, reliable, and high performing data platforms and pipeline architectures. With 10+ years as a Senior Data Engineer, I help organizations design, build, and optimize end to end data infrastructure across AWS, GCP, and Azure unlocking real time insights, analytics ready datasets, and lakehouse capabilities that power business decisions. I build production grade data solutions for clients across finance, retail, telecom, and tech supporting both startups and large enterprises. My work spans greenfield data platform builds, legacy ETL modernization, cloud migrations, and real time streaming architectures ensuring every pipeline is reliable, observable, and built to scale. I specialize in end to end Data Engineering delivery: - ETL/ELT pipeline development, orchestration, and automation (Airflow, AWS Glue, Azure Data Factory, Fivetran, Apache Beam) - Real time and streaming architectures (Apache Kafka, Apache Flink, AWS Kinesis, Google Pub/Sub, Debezium, CDC) - Data transformation and modeling using dbt (data build tool) with fully tested and documented dbt models - Cloud Data Warehouse design and optimization (Snowflake, Google BigQuery, Amazon Redshift, Azure Synapse Analytics) - Data Lakehouse architecture with open table formats (Apache Iceberg, Delta Lake, Apache Hudi) on Databricks and cloud storage - Big data processing and distributed computing (Apache Spark, Spark SQL, Trino, Presto, Athena) - Data Quality frameworks and observability (Great Expectations, Soda) Data Governance, Data Lineage, Data Catalog, and Metadata Management (OpenMetadata, DataHub) - Multi cloud data platform design across AWS (S3, Glue, Redshift, Athena), GCP (BigQuery, Pub/Sub, Cloud Storage), and Azure (Synapse, Data Lake, Data Factory) Pipeline stabilization, performance optimization, and cost reduction for underperforming data systems How I work: I follow proven data engineering principles to ensure: - Pipelines align with business goals and analytical requirements - Technical debt, bottlenecks, and data quality risks are eliminated early - Architectures remain modular, maintainable, and cloud agnostic where possible - Platforms scale reliably with data volume, team size, and workload growth I treat data infrastructure as a business enabler, not just a technical implementation. Every design decision focuses on reducing pipeline failures, improving data reliability, and accelerating time to insight for your teams. The difference I bring: You can use modern data engineering to: - Build scalable ETL/ELT pipelines that handle growing data volumes without breaking - Move from batch only to real time streaming with Kafka, Flink, and Kinesis - Migrate legacy data systems to modern cloud platforms like Snowflake or Databricks - Implement a Data Lakehouse that gives you both flexibility and warehouse grade reliability - Enforce Data Governance, Data Lineage, and Data Quality across your entire data platform - Replace fragmented, manual, or unreliable data workflows with automated, observable pipelines Let's build a data platform that actually scales.