Samiuddin Samiuddin
Senior Data Engineer @Deloitte
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WORK HISTORY
Senior Data Engineer @Deloitte
Toronto, ON, CA
As a key member of BI team, delivered the best results to the development needs, accomplished successful outcomes by working with T-SQL, SSIS, ADF2, SSAS, and Power BI.• Daily scrum meetings with Project Managers, Business Analysts, and end users/clients to gather, analyze and document the business requirements and business rules. discuss the project specs to understand the business needs.• Strong experience with SQL Server and T-SQL in implementing, maintaining developing Stored Procedures, Triggers, Nested Queries, Joins, Views, User Defined Functions, Indexes, User Profiles, Relational Databases Models, creating and updating tables and checking the database consistency by executing DBCC commands.• Migrated on-premises SQL server schemas to the cloud on Azure SQL Server and maintained databases across both on-premises and cloud deployments.• Built efficient ETL packages, using both SSIS and ADF2 pipelines for processing Fact and Dimension tables with complex transforms and SCD type 1/ type 2 changes. Build workflows to automate data flow using Python and ADF2.• Performed incremental data loading to synchronize data changes between OLTP and OLAP databases using SSIS packages, execute SQL task and merge.• Send email notifications about ETL issues reports to development team by using Send Mail Task/Script Task/Execute SQL Task along with system stored procedure to send emails.• Azure Data Factory (ADF), Integration Run Time (IR), File System Data Ingestion, Relational Data Ingestion.• Migration of on-premises data (SQL Server) to Azure Data Lake Store (ADLS) using Azure Data Factory (ADF V2).• Configured Azure platform for data pipelines, ADF, Azure blob storage and data lakes, and built workflows to automate data flow using ADF.• Combined structured, unstructured, and semi-structured data (log files, and media) using Azure Data Factory to Azure Blob Storage.
ABOUT SAMIUDDIN SAMIUDDIN
Highly Motivated Data Engineer, Data Analyst and SQL Server Developer with 5+ years of experience in professional application and database development with thorough knowledge of different phases of software development lifecycle including analysis, design, development, documentation, deployment, and system support Hands on experience with Microsoft BI (T-SQL, SSIS, SSAS), Azure (SQL Server, ADF, IaaS/SaaS/PaaS, Blob, SQL DW, ADLS2, AKV, Databricks etc.), and reporting (SSRS, Power BI, Tableau) tools. Excellent skills in creating and managing Databases, and various database objects like Tables, Views, Indexed Views, Complex Parametrized Stored Procedures, DDL/DML Triggers, Cursors, User Defined Data Types, User Defined Functions, and Indexes (clustered, non-clustered, filtered, covering, with included columns, column stored) using T-SQL. Collaborating with clients to understand their data needs and designing scalable and efficient data architectures on the AWS cloud platform. Created large scale data processing pipelines for streaming and computing with data technologies such as AWS, Snowflake, Databricks, Kafka, Spark, or similar, ensuring scalability, reliability, and fault tolerance. Built data pipelines and workflows to extract, transform, and load (ETL) data from various sources into target systems, utilizing AWS services like Amazon S3, AWS Glue, or Apache Spark Excellent at all stages of SSRS/Power BI/Tableau Reporting Life Cycle and hands on experience in creating various types of dashboards and reports. Highly skilled in Analyses Service, particularly in building both Tabular and Multidimensional models on top of DW/DM/DB and writing complex DAX and MDX queries against the models. Strong knowledge of Entity-Relationship concept, Facts and Dimension tables, slowly changing dimensions (SCD) and Dimensional Modeling (Kimball/Inmon methodologies, Star and Snowflake Schemas). Hands-on experience with Azure Data Factory V2, Data Flows, Azure Data Lake, Azure Analysis Services. Experienced in migrating data and databases from on-prem infrastructure to the Azure data lake. Raw data transferred to Azure Storage and processed by Azure functions and then stored in Cosmos DB Enhanced the functionality in data ware housing concepts (OLAP) Cube by creating KPI, Actions, Perspective and Hierarchies using SQL Server Analysis Services (SSAS) and Dimensional Modeling Techniques such as Star and Snowflake schema. Good hands-on experience in implementing dashboards,
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