I build data systems and AI-powered products that actually ship. With 5+ years across data engineering, analytics, and ML — and a recent pivot into full-stack AI development — I work at the intersection of data infrastructure and intelligent product design. My background spans AdTech (WPP/Choreograph, Coca-Cola campaigns), sports betting, GIS simulation, and independent AI app development. What I help clients with: 📊 Data Engineering & Analytics – Data modelling and transformation pipelines (dbt, SQL, BigQuery, AWS) – End-to-end analytics stacks built from scratch (GA4, Firebase, Appsflyer, Amplitude) – Data quality systems: QA strategy, dbt tests, monitoring dashboards 🤖 AI & LLM Integration – LLM automation pipelines: content generation, translation, multi-platform publishing – AI-powered product development (OpenAI API, LangChain, CrewAI, n8n) – Rapid MVP prototyping with AI-assisted development (Cursor, Copilot) 🗺️ GIS & Spatial Analytics – Geospatial data modelling (H3 grid, Kepler.gl, Carto, QGIS) – Spatial ETL pipelines, visualisation, and interactive map-based apps 📈 Product & Marketing Analytics – Web/app analytics setup (GTM, GA4, Firebase, Mixpanel) – A/B testing, funnel analysis, cohort dashboards – Attribution modelling, campaign performance analysis Recent highlights: ✅ Built a full-stack GIS simulation app solo in weeks (dbt pipeline + backend + LLM features + map UI) ✅ Delivered an AI art-to-product app: photo → wall art → 3D viewer → video → physical product ✅ Built an LLM pipeline automating multilingual content publishing across web + social ✅ Led a team of 5 data scientists on a privacy-first AdTech platform (100+ dbt models) I write clean, documented, production-ready code. I move fast — and I don't disappear after delivery.

I am Nida Ullah, a Full Stack Developer and Certified Data Engineer with 12+ years of experience. I help businesses build scalable web applications while also designing and optimizing modern data infrastructures. I cover the complete technology stack: backend development (PHP, Node.js, Laravel, CodeIgniter, Symfony), frontend frameworks (Vue.js, React.js, Next.js, jQuery), databases (MySQL, PostgreSQL, MongoDB), APIs, automation, cloud platforms, ETL/ELT pipelines, big data, and streaming systems. Whether you need a custom web application, API integrations, architecture optimization, data pipelines, or ongoing technical support, I deliver maintainable code, scalable systems, optimized workflows, and actionable documentation. What I Do (Full Stack & Data Engineering Services): ✅ Full Stack Web Development: Build scalable web applications using PHP (Laravel, CodeIgniter, Symfony, Yii, CakePHP) and Node.js (Express, Nest.js) with modern frontend frameworks like Vue.js, React.js, and Next.js. ✅ Backend Development & APIs: Develop REST and SOAP APIs, background jobs, queue workers, CRON tasks, caching with Redis/Memcached, and scalable backend architectures. ✅ Frontend Development: Create interactive, responsive UIs using Vue.js, React.js, Next.js, jQuery, Bootstrap, and work with SASS/LESS for structured UI updates. ✅ Database Design & Optimization: MySQL, PostgreSQL, MongoDB with expertise in stored procedures, views, triggers, functions, transactions, indexing, and performance tuning. ✅ DevOps & Cloud Infrastructure: Set up and manage scalable infrastructure on AWS and DigitalOcean: - EC2, Load Balancers, SSL, AMIs, Security Groups - Auto Scaling Groups (ASG) - RDS (Serverless, Dedicated, Aurora, Master-Slave setups) - Route53, S3, EBS - Elastic Cache (Redis), OpenSearch - CloudWatch with custom metrics & alerts - AWS Lambda (Serverless Computing) - DigitalOcean Apps, Load Balancers & deployment components ✅ Server Setup & Deployment Automation: Linux system administration (Ubuntu, CentOS), Docker container setup (Nginx, Apache, PHP, MySQL, MongoDB, Redis), zero-downtime deployments, composer & node package management, CI/CD-ready environments, and production-grade release automation. ✅ Mobile Application Development: Build hybrid mobile applications using Ionic Angular integrated with secure backend APIs. ✅ ETL/ELT Pipeline Development: Design and optimize data pipelines using Python, SQL, Airflow, dbt, and cloud-native tools for reliable and automated workflows. ✅ Data Warehousing & Modeling: Build and optimize warehouses on Snowflake, Redshift, BigQuery, and Azure Synapse with analytics-ready schemas and high-performance queries. ✅ Big Data & Streaming: Work with Apache Spark, Kafka, Kinesis, and Databricks for batch and real-time processing of large datasets. ✅ Cloud & DevOps Support: Deploy and manage solutions on AWS, GCP, and Azure with scalable architecture and monitoring systems. ✅ Data Integration & Automation: Connect multiple systems, APIs, and applications while automating operational workflows. ✅ Performance Optimization: Improve application speed, query performance, pipeline efficiency, and infrastructure scalability. ✅ Operational Support & Monitoring: Troubleshoot issues, monitor systems, and ensure stable production environments with clear runbooks. ✅ Documentation & Handover: Provide clean, maintainable code along with comprehensive technical documentation, mapping templates, and test cases. Deliverables You’ll Get: ✅ Fully working web applications, APIs, and backend modules ✅ Optimized databases, queries, and scalable backend systems ✅ Reliable ETL/ELT pipelines and integration scripts ✅ Automated workflows, queues, and monitoring setups ✅ Comprehensive documentation and technical handover notes How I Work: ✅ Quick scoping call to understand requirements, tech stack, and objectives ✅ Develop and test features in development or sandbox environments ✅ Deliver optimized, maintainable, production-ready solutions ✅ Optional team training for application maintenance, APIs, or data workflows Why Hire Me: ✅ Full Stack Developer & Certified Data Engineer with 12+ years of experience ✅ Strong backend foundation with modern frontend expertise ✅ Balance speed with robust, scalable architecture ✅ Deliver solutions your team can operate independently ✅ Experience across web applications, APIs, databases, cloud, ETL/ELT, and analytics systems Start now! Send a brief summary of your project requirements, current stack, and challenges. I will provide a clear plan, ETA, and technical solution. #FullStackDeveloper #WebDevelopment #PHP #Laravel #NodeJS #ReactJS #VueJS #NextJS #MySQL #PostgreSQL #MongoDB #APIs #Automation #DataEngineering #ETL #Databricks #AWS #GCP #Azure #CloudSolutions

Hi there! Fortune 500 AI Engineering Experience. I am a Applied AI Lead Data Scientist, with 7+ years of experience building production quality scalable data platforms, automating analytics workflows, and translating complex datasets into actionable business insights. My noticeable experiences are with Verizon, SiriusXM, AXA, Telefonica Spain, SK telecom, LGU+, Korea Telecom, Yapi Kredi and Optus. I specialize in end-to-end data systems from pipeline design and ETL automation to BI dashboards and predictive modeling helping businesses make data-driven decisions that boost performance and growth. For my main employer, I’ve designed and led data architecture projects across AWS, GCP, and Snowflake, built high-performance ETL pipelines with Airflow, DBT, and PySpark, and partnered with leadership to optimize customer retention, sales, and operational efficiency. - Increased client revenue by $100M+ through predictive analytics and data-driven insights - Reduced churn by 25% and boosted sales by 17% through CLV and segmentation modeling - Improved pipeline performance by 30% via automation and scalable architecture My Core Skills: Languages: SQL, Python, Data Tools: Apache Airflow, DBT, Apache Spark (PySpark), Talend Databases: PostgreSQL, Greenplum (MPP), Snowflake, BigQuery, MySQL, Firebase Visualization: Power BI, Tableau, Apache Superset, Retool Cloud Platforms: AWS (S3, EC2, Lambda), GCP Machine Learning: CLV, churn prediction, segmentation, cohort analysis DevOps: Docker, Kubernetes, Git, CI/CD I’m passionate about building data ecosystems that are reliable, automated, and business-focused so you can spend less time wrangling data and more time acting on insights. Let’s collaborate to bring innovation with AI and Data

I'm a software engineer and Retool developer with 4+ years of experience delivering high-impact solutions in fast-paced environments. I specialize in building scalable backend systems, architecting cloud-native infrastructure, and designing powerful internal tools using Retool. Currently working full-time at a YC-backed ed-tech startup (S18), I lead critical backend initiatives using Python, AWS Lambda, Django, RDS (PostgreSQL & MySQL), S3, SQS, Kinesis, Glue, and Athena. I contribute significantly to our real-time data pipeline and internal tooling efforts, helping various teams make faster, data-informed decisions. On Upwork, I help businesses build custom dashboards, operational tools, and reporting systems with Retool — from support and sales dashboards to admin portals and CRM tools. I combine strong backend expertise with a deep understanding of Retool's capabilities, enabling me to ship full-stack internal tools that solve real business problems. 🔧 What I can do for you: - Architect and build RESTful APIs using AWS Lambda or Django - Design and implement robust data pipelines and integrations - Build custom Retool UIs that connect to your databases and APIs - Create analytics and reporting dashboards tailored to your KPIs - Optimize complex SQL queries and build performant data models - Set up cloud infrastructure using AWS best practices 🧰 Tech Stack: Languages: Python, JavaScript, SQL Backend: Django, AWS Lambda Databases: PostgreSQL, MySQL, AWS RDS, Athena Cloud & Data Tools: S3, Glue, Kinesis, SQS, dbt Frontend / Internal Tools: Retool, JavaScript, Custom Components If you're looking for someone who can build and scale backend systems and deliver intuitive dashboards for your team — let’s talk. I bring a product-focused mindset and care deeply about clean, maintainable code that drives real value.

I help businesses turn messy data, manual reports, and scattered tools into clean, automated data systems that save time and improve decision-making. If your team is spending hours copying data, fixing spreadsheets, chasing reports, or dealing with broken pipelines, I can help you build a reliable data workflow from extraction to reporting. I’m a Data Engineer with 5+ years of experience building ETL pipelines, web scraping systems, data automation workflows, databases, dashboards, and API integrations for businesses that need clean, structured, and usable data. My work focuses on one simple goal: making your data accurate, automated, and easy to use. What I can help you with: ✔ Data Engineering & ETL Pipelines I build reliable ETL/ELT pipelines that extract, clean, transform, and load data from multiple sources into databases, warehouses, dashboards, or reporting systems. ✔ Web Scraping & Data Extraction I create custom web scraping systems to collect structured data from websites, directories, marketplaces, search results, product pages, job boards, real estate sites, and business listings. ✔ Data Automation Workflows I automate repetitive data tasks such as reporting, file processing, data cleaning, spreadsheet updates, API pulls, CRM updates, and scheduled data transfers. ✔ API Integrations I connect tools, platforms, CRMs, databases, and third-party APIs so your data moves automatically instead of being handled manually. ✔ Database Design & Management I work with SQL databases to organize, clean, query, and structure your data properly for reporting, analytics, and business operations. ✔ Dashboards & Reporting I prepare clean data for dashboards and reports using tools like Power BI, Looker Studio, Excel, Google Sheets, and other BI platforms. Tools & Technologies I Work With: • Python • SQL • PostgreSQL • MySQL • MongoDB • Pandas • BeautifulSoup • Selenium • Playwright • Scrapy • APIs • Airflow • dbt • Snowflake • BigQuery • AWS • Google Cloud • Power BI • Excel / Google Sheets • Automation workflows Common projects I can handle: • Build an ETL pipeline from scratch • Scrape and organize business leads • Automate manual Excel or Google Sheets reports • Clean messy CSV, Excel, or database records • Connect APIs and store data in a database • Build a database for business operations • Create scheduled data pipelines • Prepare data for dashboards • Move data from one system to another • Build web scrapers for product, pricing, or market research • Fix broken scripts, pipelines, or scraping tools Why clients work with me: • I focus on business outcomes, not just code • I keep the system clean, simple, and maintainable • I explain technical work clearly • I build solutions that save time and reduce manual work • I care about accuracy, structure, and long-term reliability Whether you need a web scraper, ETL pipeline, automation workflow, database setup, or clean reporting system, I can help you build a data solution that works smoothly and is easy to manage. Send me a message or let's jump on a call and discuss what you’re trying to automate, extract, clean, or build, and I’ll suggest the best way to approach it.

I turn messy, scattered data into clean pipelines and dashboards your team can actually trust. Over the past 3+ years building production data systems for a US-based company, I've worked across the full modern data stack and analytics engineering workflow: dbt for transformations, BigQuery for warehousing, and Airflow for orchestration. Here's how I can help: Build end-to-end ELT pipelines, from ingestion through to analytics-ready marts, using dbt, BigQuery, and Airflow Model your data with patterns that scale: star schemas, incremental models, slowly changing dimensions (SCD Type 2), and dbt tests that catch problems before your stakeholders do Write and optimize complex SQL, including rescuing slow or timing-out queries Build clear, decision-ready dashboards in Tableau, Power BI, or Streamlit Automate manual reporting and data workflows with Python and tools like n8n and Google Apps Script

I’m a Senior Data Engineer and freelance consultant with 9+ years of experience designing, building, and optimizing cloud-based data platforms. I help startups and enterprises scale their data infrastructure, improve performance, and ensure reliability, while reducing costs and improving governance. I specialize in ETL/ELT pipelines, cloud databases, serverless architectures, and infrastructure as code, working with tools like AWS, Terraform, Spark, dbt, Snowflake, Redshift and PostgreSQL/MySQL databases. I’ve partnered with clients across HealthTech, PropTech, Telecoms, Banking, Retail, Marketing, and Cybersecurity, delivering high-impact, production-ready solutions. What I Do Best ✅ Design and implement scalable ETL/ELT pipelines using Python, PySpark, and AWS ✅ Architect and manage cloud-based databases (RDBMS and cloud warehouses) for performance, security, and scalability ✅ Build serverless and event-driven architectures using AWS Lambda, SQS, SNS, Glue, Athena, EMR, and ECS ✅ Provision infrastructure reliably with Terraform and implement CI/CD pipelines (CircleCI, GitLab CI/CD, Github Actions) ✅ Implement data warehousing, modeling, and analytics solutions using Snowflake, BigQuery, dbt, and PostgreSQL/MySQL/Aurora ✅ Monitor and alert on job health with CloudWatch, Grafana, and custom dashboards ✅ Containerize applications with Docker and manage batch or service-based workloads on AWS Tech Stack ✅ Languages & Tools: Python, PySpark, Pandas, SQL, dbt, Docker ✅ Cloud & Infrastructure: AWS (Lambda, Glue, EMR, ECS, Batch, EC2, S3, SNS/SQS, ELB, DMS, DynamoDB, RDS, MWAA, API Gateway), Terraform, Serverless Architecture ✅ Databases: Snowflake, BigQuery, RDS (PostgreSQL, MySQL, Aurora), Redshift ✅ Monitoring: CloudWatch, Grafana ✅ CI/CD & Version Control: CircleCI, GitLab CI/CD, Github Actions, GitHub, GitLab

Berlin-based freelance data engineer helping teams automate reporting workflows, improve data reliability, and fix messy SQL/dbt pipelines. Experienced in building production-grade systems across energy, banking, and AI-driven applications. Core stack: - Python - SQL - dbt - BigQuery - GCP Available for freelance and part-time engagements. I enjoy solving messy operational problems and building reliable systems that reduce manual work for engineering and business teams.

I specialize in cloud data architecture, scalable ETL/ELT pipelines, and lakehouse implementations for businesses that require reliable, high-performance data systems. My focus is helping teams migrate from legacy on-premise systems to the cloud, resolve slow query performance, and build robust data pipelines that scale without latency or data quality issues. If your data is delayed, inconsistent, or siloed, I help identify the root cause and implement an architecture that aligns with modern data engineering best practices. 𝐖𝐇𝐀𝐓 𝐈 𝐇𝐄𝐋𝐏 𝐖𝐈𝐓𝐇 • Cloud data migrations (On-premise to AWS/Snowflake) • Lakehouse architecture design (S3, Glue, Athena) • Streaming and batch pipeline development (Kinesis, Lambda, Airflow) • dbt modeling and SQL-based transformations • Data governance and cataloging (DataHub) • Data quality checks and automated testing • BI enablement and self-service dashboards (Tableau, Looker) 𝐏𝐈𝐏𝐄𝐋𝐈𝐍𝐄𝐒 & 𝐀𝐑𝐂𝐇𝐈𝐓𝐄𝐂𝐓𝐔𝐑𝐄 I build scalable data pipelines using Python, Apache Airflow, and dbt to connect disparate data sources with modern cloud data warehouses. These pipelines automate data ingestion, transformation, and orchestration while maintaining strict data quality and governance standards. All solutions are containerized with Docker, deployed via CI/CD, and designed to support long-term data reliability and self-service analytics. 𝐖𝐇𝐎 𝐈 𝐖𝐎𝐑𝐊 𝐖𝐈𝐓𝐇 I work with startups, e-commerce companies, and established enterprises that rely on data for business intelligence, operational reporting, and strategic decision-making. Many clients come to me after experiencing high data latency, failed cloud migrations, or unstable pipelines caused by poor architecture or lack of governance. My role is to correct those issues and implement a clean, optimized data stack that works reliably in production. 𝐀𝐏𝐏𝐑𝐎𝐀𝐂𝐇 & 𝐑𝐄𝐋𝐈𝐀𝐁𝐈𝐋𝐈𝐓𝐘 My approach is architecture-first and practical. I start by understanding your data use case, volume, and analytics goals, then align your setup with cloud best practices and data governance standards. From there, I handle the technical implementation, pipeline orchestration, and optimization required to support scalable data operations. As a Top Rated ⭐⭐⭐⭐⭐ freelancer with 100 percent Job Success on Upwork, I prioritize correct implementation, clear communication, and solutions that reduce long-term technical debt for my clients. If you are planning to migrate to the cloud, struggling with slow data pipelines, or need robust and automated data engineering workflows, feel free to reach out. I'm happy to review your data stack and recommend the best technical approach.

I build the data pipelines, transformation layers, and automated reporting that companies need but don't have a data team to build. If you're stuck on manual spreadsheets or can't get reliable numbers out of your systems, that's the problem I solve. 10+ years across fintech, telecoms, and research — usually as the sole data function at early-stage companies, owning everything from raw ingestion to clean models to the dashboards stakeholders actually use. What I typically build: • Production pipelines pulling from your CRM, APIs, or databases (dlt, Prefect, Airflow) into PostgreSQL • A documented dbt transformation layer so your numbers are trustworthy and repeatable • Automated reporting that replaces the weekly manual spreadsheet grind • One-off analysis when you need a decision backed by data Core stack: SQL, Python, dbt, PostgreSQL, dlt, Prefect/Airflow. AWS Certified Solutions Architect, PhD in Cognitive Neuroscience, and currently consulting for the University of Oxford on an AHRC-funded research project — so I'm comfortable with messy real-world data and non-technical stakeholders. If you want a quick call to work out whether I'm a fit, message me.