Muhammad Saad Tahir Email & Phone Number

Vancouver, British Columbia, Canada

Vancouver, British Columbia, Canada

• Design, build and maintain a highly scalable pipeline (end-to-end) for large volumes of complex data processing and analysis in Google Cloud Platform.
• Develop Apache NiFi based data pipelines to ingest and wrangle incremental data from AWS RDS and load it in BigQuery.
• Orchestrate big data architectures and ETL pipelines using Airflow in GCP Cloud Composer.
• Build pipelines to and from external sources like FTP/SFTP servers to GCP BigQuery, GCS, SQL server, Cloud based database systems.
• Optimize complex data transformation workflows using Google Cloud Dataprep, leveraging advanced wrangling techniques and seamless integration with BigQuery for robust data analytics.
• Design, develop, and maintain robust and scalable data pipelines using Python, PySpark, and ETL (Extract, Transform, Load) techniques, ensuring data security and performance.

• Leading the design and development of cloud & multi-cloud Big Data architectures/workflows on Amazon Web Services (AWS) and Microsoft Azure.
• Extensive expertise in developing Big Data solutions on Amazon Web Services (AWS), utilizing services such as EMR, EC2, Glue, RDS, S3, Redshift, Step Functions, CloudFormation, Lambda, ECR, Athena, IAM, MWAA, Kinesis.
• Skilled in design and development of data pipelines on Azure, utilizing services like Data Factory, Synapse, Databricks, Redis, Datalake Storage Gen2, Event Grid, Azure Functions, Azure SQL Database.
• Design and re-design significant data pipelines, ensuring our clients derive optimal value from AWS & Azure services by assessing cost/performance trade-offs.
• Automating data workflows, orchestrating data pipelines and setting up alerting systems to identify and address issues proactively on AWS and Azure.
• Deploying and maintaining entire data infrastructure on AWS and Azure using services like Cloud Formation and Terraform.

• Designed and implemented end-to-end data processing pipelines using Apache Spark, Hadoop, Hudi and other Big Data technologies.
• Implemented AWS Lambda functions in Python to invoke Sqoop and PySpark jobs on AWS EMR. Utilized AWS Step Functions to orchestrate the entire ETL process.
• Managing large-scale Redshift clusters with expertise in data distribution styles, sort keys, and workload management. Fine-tuning Redshift query performance through query optimization.
• Developed Curation jobs in Apache Spark (EMR, Glue, Databricks) to integrate data ingested from multiple sources, apply schema, clean, and convert it into delta and Hudi tables for enhanced processing efficiency.
• Implemented Extract, Transform, and Load (ETL) jobs in PySpark to transform curated data into analyzed datasets, providing valuable insights for the business.
• Devised strategies to maximize cloud compute cluster resources (EMR, Databricks) for improved big data ETL job performance and cost-effectiveness.

Lahore, Pakistan

• Internship in Supply Chain Department of Coca Cola Beverages Plant Limited.
• Focused on Waste Water Plant process and automation, gaining valuable insights into the operations of machinery and processes in RGB, PET Production Lines, and other manufacturing areas.
• Conducting monthly audits for Machine Safeguarding, Fall Protection, and Fire Control, ensuring compliance with KORE requirements. Received a 90% evaluation score from my supervisor for my efforts in this area.

Bachelor Of Science - Bs, Electrical And Electronics Engineering

Fsc, Pre-Engineering, A+ (1013/1100)