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 am a Data Expert with over 11 years of experience specializing in data engineering and analytics. My background includes five years with a Big4 firm, where I honed my skills in SQL, data modeling, ETL/ELT pipelines, and data visualization. I have a proven track record of delivering actionable insights and driving process efficiency for Fortune 500 clients across diverse industries such as retail, finance, and technology. I excel in stakeholder collaboration and root cause analysis, turning complex data into compelling stories that empower data-driven decision-making. If you need a seasoned analytics engineer who can translate data into strategic business value, I would love to collaborate on your project.

I am a Senior Data Engineer with over six years of experience in building robust data models, transformation layers, and analytics-ready datasets that drive critical business decisions. My expertise in SQL, dbt, Snowflake, Databricks, and Python allows me to turn complex business questions into reliable data products. I thrive on collaborating with product, marketing, and operations teams to ensure data is both actionable and scalable. I am well-versed in modern AI-assisted workflows and prioritize governance through meticulous documentation, testing, and metric definition. If you are looking for a data professional who can enhance your analytics capability and streamline your processes, let’s connect and discuss how I can elevate your data strategy.

I help logistics and e-commerce businesses turn scattered, messy data into automated Python ETL pipelines and real-time Power BI dashboards. My focus is eliminating your manual reporting hours and building a single reliable source of truth for your operations. WHAT I HAVE BUILT FOR CLIENTS: • Built end-to-end ETL pipelines using Python and PostgreSQL that pull, clean, and model raw operational data into star-schema databases optimized for Power BI reporting. • Engineered a multithreaded Python automation system that parsed complex 27MB AutoCAD/DXF engineering files and extracted structured data into clean Excel reports. This reduced manual data entry from hours to seconds. • Upgraded static regex algorithms with robust Python logic to dynamically process varying alphabetical market codes. This bulletproofed the extraction pipelines against non-standard labeling. • Developed interactive Power BI dashboards connected to live PostgreSQL backends. This gave operations managers real-time KPI visibility they previously had to track manually in spreadsheets. MY WORKFLOW: I start with your data sources and business questions to design the right data model. Next, I build clean documented pipelines and deliver working outputs, rather than just raw code you have to figure out yourself. I communicate clearly throughout every stage and never close a contract until the solution is running perfectly. CORE STACK: Python (ETL, automation, multithreading), SQL, PostgreSQL, Power BI, dbt, Data Modeling, Database Architecture, ETL Pipeline design, Data Extraction, Business Intelligence. NEXT STEPS: If your team is losing hours to manual data work or making decisions without proper reporting, send me a message. I will reply within 24 hours with a clear plan on exactly how to fix 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 build analytics pipelines and data systems that turn raw data into reliable dashboards and business metrics. If you're working with Shopify, SaaS data, or multiple data sources, I can help you structure your data properly and deliver clear, actionable insights. What I can help you with: Build or fix data pipelines (Python, SQL) dbt transformations (staging → marts) Data modeling (facts, dimensions, SCDs) Ecommerce analytics (orders, customers, AOV, LTV) Dashboard development (Metabase or similar tools) Debugging broken or inconsistent analytics setups I focus on building clean, maintainable, and cost-efficient solutions—from small pipelines to more structured analytics systems. Recent work: Built a containerized Shopify analytics system with incremental ingestion, dbt transformations, orchestration (Dagster), and dashboards Tech stack: dbt, SQL, BigQuery, Python, Dagster Reach out to me for a free consultation.

I help businesses build reliable data systems that replace manual reporting, messy spreadsheets, and disconnected tools with clean, automated data pipelines. I specialize in data engineering, analytics infrastructure, and reporting automation. I’ve built production data workflows across finance, lending, operations, marketing, and customer analytics, from raw source data to clean warehouse models, dashboards, and recurring business reports. What I can help with: • ETL/ELT pipeline development using SQL, Python, dbt, Prefect, Airflow, AWS, GCP, Snowflake, and BigQuery • Data warehouse design, dimensional modeling, metric definitions, and BI-ready datasets • API, SFTP, CRM, ERP, spreadsheet, and database integrations • Financial reporting automation, P&L reporting, KPI dashboards, and executive reporting • Data quality checks, pipeline monitoring, documentation, and maintainable handoff

Data Engineer with a strong background in Computer Science and Mathematics, currently pursuing a Master's in Databases and Software Technologies. I manage the entire data lifecycle, specializing in the transition from legacy on-prem systems to modern cloud architectures. My expertise lies in bridging the gap between hybrid infrastructures, maintaining SSIS/SQL Server environments while architecting scalable pipelines in Azure, Snowflake, and Databricks. Core Technical Focus: - Specialized in using modern data stack (Azure, Snowflake, dbt, Databricks, and Power BI) to turn raw data into insights. - Management and optimization of Azure data environments. - Building reliable, cloud-native pipelines that replace or support on-prem bottlenecks. I focus on creating optimized data environments that are built on long-term scalability.

I’m Abdelrahman Ata, a passionate Data Engineer with hands-on experience building scalable pipelines for sports, finance, and e-commerce clients. Skilled in Python, SQL, Apache Airflow, dbt, and cloud platforms like GCP and Snowflake, I craft end-to-end solutions from ingestion to delivery. With a Computer Engineering degree from Mansoura University and projects like the Formula 1 Data Pipeline, I deliver actionable insights with precision. Plus, I excel in web scraping and task automation to streamline workflows. Let’s turn your data challenges into opportunities—hire me for reliable, innovative results!

🌟 About Me: Hello! I’m a passionate Data Engineer with a knack for transforming complex data systems into streamlined, user-friendly operations. With a strong background in cloud migrations and data engineering, I’ve led projects for major companies like Carrefour and Enovos, achieving significant improvements in efficiency and scalability. 🚀 🔍 What I Do: I specialize in: • Cloud Migrations 🌩️: Transitioning legacy systems to AWS, Azure, and GCP with minimal downtime. • Data Engineering 🛠️: Building and optimizing data workflows, from ingestion to analytics. • Real-Time Data Solutions ⏱️: Implementing systems that offer immediate insights to drive business decisions. 💼 Key Achievements: • Led the cloud migration project at Carrefour, enhancing operational resilience and reducing costs. • Designed and executed a state-of-the-art real-time monitoring system for industrial compressors at AF Compressor, enhancing global operations. • Developed a comprehensive data platform at Enovos that aligns energy trading data with customer distribution, greatly improving strategic decision-making. 🎯 Why Choose Me? I bring a unique blend of technical expertise, strategic vision, and a collaborative spirit to every project. My goal is to not only meet your data needs but to exceed them, ensuring that your business is not just running, but thriving. Let’s connect and take your data systems to the next level! 👋