Hammad Ahmed

• 6 years of experience in Data Analytics/Data Engineer with diversified tools and technologies in advisory roles • Strong Data Modeling Concepts such as Logical and Physical Data Modeling using Dimension Modeling and Star Schema. • Designed, deployed and maintained data pipelines using AWS Glue, Lambda, and Step Functions. • Developed ETL processes to convert and import data from various sources into Redshift using AWS Glue. • Apache Spark was used for distributed data processing and analysis. • A data warehouse solution was implemented and maintained on AWS using Redshift for analytics services • Data workflow design and orchestration using AWS Step Functions and Lambda functions • Familiar with the latest AWS services and data engineering best practices to increase productivity and efficiency • Hands on Experience in Aws services like EC2,S3,EBS,IAM,SQS,RDS,SNS,APIGateway,Lambda ,Glue, Cloudwatch, VPC • Leveraged dbt to create data models and transformations in Amazon Redshift, streamlining analytics workflows and providing a structured layer for SQL-based data transformations • Collaborated with cross-functional stakeholders to elicit and analyze business requirements • Designed and implemented TSQL queries for reporting and complex solution development • Maintained complex T-SQL queries, views and stored procedures in multi-database environment. • Create and managed ETL pipeline using SSIS • Experience on Migrating SQL database to Azure Data Lake, Azure data Lake Analytics, Azure SQL Database, Data Bricks and Azure SQL Data warehouse and Controlling and granting database access and Migrating On premise databases to Azure Data lake store using Azure Data factory • Strong Knowledge of Conventional DWH end to end implementation and Big Data Architecture as well. • Deploy ETL Python script on Docker container using ECR and ECS and On on-premises • Strong understanding of existing ETL tool business logic rules, data sources, convert same ETL jobs to Talen arch, and resolve production issues with ETL workflow using Airflow. • Strong Understanding of Spark, Hive, YARN and Streaming Use Cases using Spark. • Make ETL in Glue using python shell • Strong Experience in communicating with relevant stakeholders in requirement analysis and