Hire the Best Big Data Engineers
in Pakistan

Most data pipelines don't fail loudly. They rot quietly. A job starts silently skipping rows. A dashboard still loads, but the numbers stopped matching reality weeks ago. The warehouse bill creeps up because nobody ever tuned the queries. Eventually someone exports to a spreadsheet "just to be sure" and that's the moment the system stopped being trusted. That's the work I do: build data pipelines and warehouses people actually rely on, and fix the ones that quietly stopped working. Over the last 3 years I've delivered 55+ data projects across finance, healthcare, energy, and e-commerce, from one-off ETL jobs to platforms processing billions of records a day. I work GCP-first (BigQuery, Airflow, dbt, Dataflow), and I'm comfortable across AWS, Postgres, and the messy real-world stack most teams actually have. What I build: - End-to-end ETL/ELT pipelines in Python, SQL, Airflow, and dbt - BigQuery / Snowflake / Redshift warehouses and data models that stay clean as they grow - Migrations off legacy jobs and on-prem databases — without losing data in the move - Metabase, Looker Studio, and Power BI dashboards your team will actually open - Query and cost optimization when your warehouse bill stops making sense - API integrations with proper logging, retries, and checkpoints, so failures are visible instead of silent You probably need me if: - Your pipelines break and you hear it from a stakeholder, not an alert - Reports run slow, cost too much, or quietly disagree with each other - A previous developer left and nobody fully understands the setup anymore - You're scaling fast and the current data stack is starting to crack A few real results: - Architected pipelines processing 5B+ records daily at 99% reliability - Cut a client's warehouse costs ~50% by migrating legacy jobs to BigQuery - 4× throughput and 70% faster ingestion on an API pipeline pulling 2K+ domains a day - 40% faster pipeline runs through Airflow optimization How I work: a clear yes/no on feasibility before you commit, regular updates, and no disappearing mid-project. Most clients come back — usually because fixing one thing surfaces the next. If that sounds like your situation, send a short note on what's breaking or what you're trying to build, and I'll tell you straight what it'll take.

I'm a results-driven Senior Data Engineer specializing in building cloud-native data pipelines and architectures that transform raw data into actionable business insights. With 100% job satisfaction and a 5-star rating, I deliver solutions that exceed expectations. What I Bring: Cloud Expertise: Azure, GCP, and AWS with deep experience in Databricks, BigQuery, and Data Factory Real-Time Processing: Built streaming pipelines reducing reporting latency from hours to minutes Enterprise Scale: Consolidated 50+ data sources, processed 100M+ daily transactions, and supported 1000+ users Architecture Design: Expert in Lakehouse, Medallion, and Star Schema implementations with strong data governance Proven Results: Reduced reporting latency by 98% through real-time pipeline optimization Improved query performance by 40% with strategic data modeling Achieved 35% increase in compliance reporting accuracy Delivered zero-downtime deployments with automated CI/CD I partner closely with stakeholders to understand business needs and deliver data solutions that drive decision-making. Whether it's building real-time analytics platforms, implementing data governance, or optimizing existing pipelines, I focus on scalable, maintainable solutions. Let's discuss how I can help transform your data into a strategic asset.

Data Engineer with 8+ years of experience designing scalable ETL pipelines, cloud data warehouses, and BI solutions using Power BI, Looker, Looker Studio and Tableau that turn raw data into reliable, decision-ready insights. I help businesses automate reporting, reduce manual work, and build high-performance analytics on GCP, Azure, and AWS. 𝐃𝐚𝐭𝐚 𝐄𝐧𝐠𝐢𝐧𝐞𝐞𝐫𝐢𝐧𝐠: • Expertise in building efficient ETL processes with Apache Airflow, Cloud Composer, and Dataform. • Skilled in GCP, Azure, and AWS, with expertise in key services like BigQuery, Cloud Functions, Synapse, and Redshift for optimized data warehousing • Proficient in data modeling and data transformation with DBT for clean, organized datasets. • Experienced with Docker for containerization and Google Cloud Run for scalable deployments. • Skilled in real-time data processing using Google Pub/Sub and data management with Data Lake. 𝐀𝐏𝐈 & 𝐃𝐚𝐭𝐚 𝐈𝐧𝐭𝐞𝐠𝐫𝐚𝐭𝐢𝐨𝐧: • Data extraction using Screaming Frog and DataforSEO. • CRM and marketing data integration with APIs like Apollo, HubSpot, and Facebook. • Search analytics expertise with GA4, Google Search Console, and SerpAPI. • Comprehensive API management for seamless, cross-platform data connectivity. 𝐃𝐚𝐭𝐚 𝐀𝐧𝐚𝐥𝐲𝐬𝐢𝐬: • Skilled in Power BI, Looker, and Tableau for creating clear, insightful dashboards. • Proficient in Python for data analysis, statistical modeling, and visualization. • Advanced SQL skills for efficient data querying and manipulation. • Experienced in data preparation and transformation, ensuring high-quality analytics. My strong communication and collaboration skills ensure smooth teamwork and project management. Flexible with working hours, I adapt to meet specific client needs and timelines.

Hello! I'm Tayyab , Top Rated Plus Data Solutions Expert. With 10+ years of hands-on experience as a Data Engineer, I specialize in Data Modeling, ETL/ELT Development, Data Warehousing, and Data Lakehouse solutions. I’ve successfully designed and developed 100+ dashboards using Power BI, Tableau, and Looker Studio. and created more than 20+ Data Warehouse during these 9 years of Data Engineering which includes Azure, GCP, AWS, Databricks, Snowflake, DBT and much more. My expertise extends into Machine Learning and Data Science, making me a one-stop solution for all your data needs. Why Work with Me? ⭐ Over 50 clients with 5-star ratings ⏱ 3000+ hours logged on Upwork My Expertise Includes: ✔ Google Cloud: Google Sheets, Analytics, Tag Manager, BigQuery, Cloud Function, Dataflow, Pub/Sub, Storage Bucket, Looker ✔ Microsoft Azure: Datalake Gen2, Blob Storage, Data Factory, Synapse, Analysis Services, SQL Data Warehouse, Event Hub, Databricks ✔ Microsoft: T-SQL, SSIS, SSAS, Power BI ✔ Amazon Web Services (AWS): S3, DynamoDB, Kinesis, RDS, Redshift, Glue, Lambda ✔ Other Tools: Databricks, Snowflake for Delta Lakehouse, DBT, SQL, Python I’ve designed and implemented data architecture for Fortune 50 to 500 companies, providing customized solutions that meet complex data challenges. If you're looking for a data expert to help transform your data into actionable insights, let’s connect! I'm just one message away and excited to work with you.

𝗬𝗼𝘂𝗿 𝗯𝘂𝘀𝗶𝗻𝗲𝘀𝘀 𝗿𝘂𝗻𝘀 𝗼𝗻 𝗱𝗮𝘁𝗮 - 𝗯𝘂𝘁 𝗼𝗻𝗹𝘆 𝗶𝗳 𝘁𝗵𝗮𝘁 𝗱𝗮𝘁𝗮 𝗶𝘀 𝗮𝗰𝗰𝘂𝗿𝗮𝘁𝗲, 𝗮𝗰𝗰𝗲𝘀𝘀𝗶𝗯𝗹𝗲, 𝗮𝗻𝗱 𝗮𝗰𝘁𝗶𝗼𝗻𝗮𝗯𝗹𝗲. I help companies build scalable data platforms that eliminate manual reporting, automate complex workflows, and transform raw data into meaningful business insights. Whether you're starting from disconnected spreadsheets or modernizing an existing cloud infrastructure, I design data solutions that are reliable, efficient, and built to scale. With 4+ years of hands-on experience, I've developed enterprise-grade pipelines, implemented Medallion Architecture, optimized large-scale Spark workloads, automated data ingestion from multiple sources, and delivered analytics-ready datasets for healthcare, insurance, and enterprise organizations. 𝗧𝗲𝗰𝗵𝗻𝗶𝗰𝗮𝗹 𝗘𝘅𝗽𝗲𝗿𝘁𝗶𝘀𝗲: ▶End-to-end ETL/ELT pipeline development ▶Azure Databricks & PySpark data engineering ▶Azure Data Factory & workflow automation ▶Data migration and cloud modernization ▶Data warehousing & Medallion Architecture ▶SQL optimization & performance tuning ▶Power BI dashboards & business intelligence ▶Data integration using APIs and cloud services ▶Data quality, governance & validation ▶BigQuery, Snowflake & Azure SQL solutions Every successful data project starts with understanding the business problem; not just the technology. Before writing a single line of code, I evaluate your existing architecture, identify bottlenecks, and design a solution that improves performance, reduces operational costs, and delivers trusted data for decision-making. 𝗜𝗳 𝘆𝗼𝘂 𝗻𝗲𝗲𝗱 𝗮 𝗗𝗮𝘁𝗮 𝗘𝗻𝗴𝗶𝗻𝗲𝗲𝗿 𝘄𝗵𝗼 𝗰𝗮𝗻 𝗯𝘂𝗶𝗹𝗱 𝘀𝗰𝗮𝗹𝗮𝗯𝗹𝗲 𝗽𝗶𝗽𝗲𝗹𝗶𝗻𝗲𝘀, 𝗼𝗽𝘁𝗶𝗺𝗶𝘇𝗲 𝗰𝗹𝗼𝘂𝗱 𝗱𝗮𝘁𝗮 𝗽𝗹𝗮𝘁𝗳𝗼𝗿𝗺𝘀, 𝗮𝗻𝗱 𝘁𝘂𝗿𝗻 𝗰𝗼𝗺𝗽𝗹𝗲𝘅 𝗱𝗮𝘁𝗮 𝗶𝗻𝘁𝗼 𝗯𝘂𝘀𝗶𝗻𝗲𝘀𝘀 𝘃𝗮𝗹𝘂𝗲, 𝗹𝗲𝘁'𝘀 𝗱𝗶𝘀𝗰𝘂𝘀𝘀 𝘆𝗼𝘂𝗿 𝗽𝗿𝗼𝗷𝗲𝗰𝘁.

Messy data slowing your team down? I build scalable ETL/ELT pipelines and modern cloud architectures on Azure, Databricks, Fabric, and Snowflake that turn raw, chaotic data into clean, analytics-ready systems fast and reliably. I bridge the gap between fragmented data sources and production-grade dashboards, seamlessly adapting to your existing infrastructure rather than forcing an expensive rebuild. What I Can Help You With: Data Warehouse & Lakehouse Architecture: Implementing Medallion design patterns (Bronze → Silver → Gold) using Delta Lake, Microsoft Fabric OneLake, and Snowflake. Scalable ETL/ELT Ingestion: Building automated, metadata-driven pipelines via Azure Data Factory, Fabric Pipelines, Databricks (PySpark/SQL), and dbt. Real-Time Data Streaming: Architecting low-latency workflows using Apache Kafka, Azure Event Hubs, and streaming engines. Database Design & Optimization: Performance tuning, indexing, and data modeling for PostgreSQL, Azure SQL, and cloud warehouses. Proven Project Highlights: Microsoft Fabric Incremental Pipeline: Built a control-table pattern using Get Metadata, Lookup, and ForEach loops to orchestrate zero-duplicate, quarterly ingestion from SharePoint into OneLake via Dataflow Gen2. Azure/Databricks Streaming: Developed a restaurant analytics platform processing 80,000+ events/day, cutting reporting lag from 6 hours to under 3 minutes. Kafka/Snowflake Pipeline: Engineered a real-time stock market data pipeline tracking 120+ tickers with under 8 seconds end-to-end latency. I write clean, documented code your team can maintain long-term and provide transparent daily updates. Message me with your data challenge and I’ll walk you through exactly how to solve it.