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Click here or scroll down to respond to this candidateABIDOV DOSTONEMAIL AVAILABLE PHONE NUMBER AVAILABLE WINTER GARDEN FL Street Address
With about 8 years of extensive professional expertise in various facets of data management, including database design, data warehousing, data lakes, OLTP (Online Transaction Processing), OLAP (Online Analytical Processing), ODS (Operational Data Stores), Data Volts, and Analytical Reporting Systems, I bring a wealth of experience to the table. Excel in crafting intricate SQL data models and have a strong proficiency in utilizing tools such as ADF (Azure Data Factory), SSIS (SQL Server Integration Services), Azure Synapse, Power BI, and Databricks Notebooks with Python and SQL. I'm also well-versed in developing stored procedures and functions that align with business needs. Possess a robust analytical mindset and a knack for solving complex problems. I'm deeply passionate about leveraging data to drive decision-making processes and am dedicated to devising innovative solutions to address business challenges. Hands-on experience in handling and processing vast volumes of data, ensuring its accessibility and usability for various analytical purposes. Deep understanding of Apache Spark, a crucial component in big data processing. I can harness its capabilities to process and analyze large datasets efficiently. Skilled in optimizing data workflows within Databricks, ensuring that data is processed and transformed efficiently to meet the specific needs of the business.TECHNOLOGY STACKT-SQL, PL-SQL, MySQLETL via SSIS/ADF/Redpoint/Talend/AWS GluePower BI, Tableau, Domo, Crystal Reports, SSRSOLTP, OLAP, Data Warehouse Data Marts, ODSAzure SQL PAAS/SAAS/IAAS, Azure Data Lake, Databricks, Azure Synapse, Function App, Logic App, Azure Runbooks, Azure Data FactoryC#, Python, PowerShellGitHub, Git Bash, CICD pipelines, Terraform.Azure DevOps, Jira, Agile Methodology, WaterfallAWS RDS MySQL, RDS Oracle, Redshift, S3, EC2DAX, DAX Studio, MDX, Ervin, Visual Studio, SSDT, SSMS, ER Studio, MS Visio, Azure Data Explorer, Jupiter NotebookWORK EXPERIENCECLOUD DATA ENGINEER DELOITTE, NY 2020 FEB - PRESENTCollaborated closely with agile teams to conceptualize, construct, test, deploy, and provide support for technical solutions within a comprehensive set of full-stack development tools and technologies.Conducted thorough research on emerging technologies to evaluate their potential applications within the realm of data visualization.Worked collaboratively with Product Analysts and business stakeholders to elucidate requirements and subsequently translated these into precise technical specifications.Actively participated in business analysis and technical design sessions, engaging with both business and technical teams to craft comprehensive requirement documents and ETL (Extract, Transform, Load) specifications.Crafted and shared Power BI reports and dashboards tailored to meet specific business needs and on-demand requests. Developed DAX (Data Analysis Expressions) functions for diverse fact-based calculations to optimize data presentation within Power BI.Produced scorecards featuring executive summary dashboards that visually represented industry Key Performance Indicators (KPIs) using Power BI. Employed Power BI gateway to ensure real-time synchronization of dashboards and reports with on-premises data sources.Leveraged reverse engineering techniques in Erwin to gain insights into the existing data model of the data warehouse. Employed Relational and Dimensional Data Modeling Techniques to design ERWIN data models.Orchestrated the creation of Data Lakes and Data Warehouse solutions by harnessing a combination of Azure Data Factory, T-SQL, and Azure Data Lake Analytics. This included the ingestion of data into Azure Data Lake and its subsequent processing using Azure Databricks.Designed and implemented data pipelines within Azure Data Factory to facilitate the Extract, Transform, and Load (ETL) processes from diverse sources, including universal data and on-premises Oracle.Constructed a robust Data Storage solution incorporating Azure SQL Database, Synapse SQL Pools, Spark Pools, Kusto Log Workspaces, Azure Data Lake Storage, and other pertinent components.Collaborated with data scientists and analysts to operationalize machine learning workflows within Databricks.Implemented real-time data processing and streaming analytics using Databricks Streaming capabilities.Demonstrated expertise in using Databricks to work with big data, including Apache Spark for distributed computing.Leveraged Databricks for data cleansing, feature engineering, and data enrichment tasks.Extensively utilized Azure DevOps to construct Continuous Integration and Continuous Deployment (CI/CD) pipelines for numerous projects, ensuring streamlined development and deployment processes.Integrated ADF with various data sources and sinks, including cloud-based and on-premises databases, data lakes, and APIs.Implemented complex data transformation logic using ADF Data Flow activities and custom data transformations.Utilized Azure Data Factory Data Flows to handle schema mapping, data type conversion, and data enrichment.Orchestrated data pipeline execution schedules and dependencies using ADF's scheduling and triggering capabilities.Developed data orchestration workflows in ADF, enabling data movement and processing across Azure services.Skillfully set up and configured various Azure Services (Virtual Machines, App Services, Azure Data Factory, Databricks, and Data Lake) in accordance with the distinct requirements of each project.Pioneered the implementation of real-time data pipelines using Azure Stream Analytics, sourcing data from Apache Kafka APIs and storing it in Azure Cosmos DB.Employed Azure Stream Analytics pipelines to extract, filter, and process data, as well as perform SQL queries tailored to the organization's specific needs, before storing it in Azure Data Lake Storage.Devised Azure Stream Analytics pipelines to facilitate real-time data analysis, ultimately storing the results in Azure Data Lake Storage.Designed and developed comprehensive reports and interactive dashboards using Power BI, drawing upon data stored in Azure Data Lake Storage, and subsequently published them for user access.SQL BI ENGINEER Bloomin' Brands, TAMPA, FL 2018 MAY 2020 FEBPartnered with business teams to get business requirements, execute, and deliver reporting and advanced analytics solutions aimed at enhancing business performance.Maintained vigilant oversight of data quality, proactively addressing any issues and instituting automated data quality monitoring processes to enhance auditing capabilities.Provided guidance on data collection best practices and offered consultation to product teams during the planning phases of new tools and products.Worked in close conjunction with analysts and user representatives to facilitate the technical delivery of reporting solutions.Engaged actively in pivotal client meetings, including requirement sessions, system demonstrations, user acceptance testing, and end-user training.Demonstrated proficiency in Power BI and various BI components such as Oracle, SQL, SSIS, SSRS, and SSAS.Formulated SQL Database Objects, including Tables, Indexes, Views, Stored Procedures, and User-defined functions, tailored to the specific needs of each project.Developed intricate T-SQL queries, Stored Procedures, and User-Defined Functions within SQL Server.Crafted SSIS packages, overseeing aspects such as package security, execution, and monitoring. These packages were designed to validate, extract, transform, and load data into data warehouse databases.Orchestrated the transfer of data from AWS S3 Buckets to Azure Data Lake Storage (ADLS).Established a linked service connecting Azure Data Factory and Azure Databricks to execute custom PySpark code.Spearheaded data migration from Azure Blob Storage to Snowflake by implementing Snow pipes.Visualized insights through Power BI, using data from Azure SQL Database via a Synapse link.Designed a trigger within Azure SQL Database to dispatch confirmation alerts to end-users through Azure Notification Hubs upon the processing and approval of claims.Monitored end-to-end infrastructure events and notifications through Azure Kusto Log Analytics.Managed code reviews and version control efficiently via Azure DevOps Repos.Applied data normalization techniques to optimize the performance of ADF data pipelines handling large data volumes.Constructed Data Warehousing solutions leveraging Azure cloud resources, including Azure Data Lake Storage (ADLS), Azure Data Factory, Azure Databricks, PySpark, Azure SQL Database, Cosmos DB, Blob Storage, PowerBI, Synapse, Kusto Log Analytics, and Azure DevOps Repos.Overseeing and enhancing the Power BI environment, including ongoing changes and active backlog management.Imported data from Oracle DB, SQL Server DB, and Azure SQL DB into Power BI for report generation.Conducted data cleansing tasks within Power BI, employing techniques like merge queries, append queries, and data column sorting to align datasets with report requirements.Formulated DAX Queries to create computed columns, applied DAX calculated measures and columns, showcasing robust data analysis practices within Power BI. Scheduled automatic refreshes and configured refresh schedules within the Power BI service.Created various Power BI reports encompassing charts, filters, scorecards, drill-down and drill-through features, cascading reports, and parameterized reports, all with meticulous attention to conditional formatting.SQL DEVELOPER Nielsen, TAMPA, FL 2016 AUG - 2018 MAYBuilt data warehouse, performing logical and physical data modeling, and mapping data dictionaries.Developed various SQL database objects, including user-defined functions, views, instead-of triggers, and employed indexes to achieve diverse tasks.Applied Dimensional Data Modeling techniques, employing both Star and Snowflake schemas for Fact and Dimension tables.Engaged in comprehensive testing and optimization of report performance. Conducted SQL performance tuning by analyzing indexes, optimizing joins, monitoring query statistics, and examining execution plans using tools such as SQL Profiler, Query Analyzer, and SSMS.Designed SSIS packages responsible for extracting data from existing OLTP databases and transferring it to the new data warehouse. These packages included a variety of transformations like Lookup Transformations, Merge Joins, Fuzzy Lookups, Derived Columns, Conditional Splits, and Data Conversions using multiple Data Flow tasks.Configured SSIS Package Configurations and implemented Event Handlers for On Error, On Warning, and On Task Failed Event Types. Created complex packages with robust error handling and package logging, storing the results in SQL tables and log files.Automated SSIS packages using SQL Server Agent Jobs, Windows Scheduler, and third-party tools to enhance efficiency.Monitored and debugged complex packages using Data Viewers Grids and Debugging techniques.Maintained ETL packages and optimized ETL processes in alignment with SQL Server best practices.Played a key role in creating intricate SSRS (SQL Server Reporting Services) reports, including sub-reports, linked reports, charts, drill-through/drilldown reports, and also developed numerous Report Models empowering users to create their own reports.Deployed solutions on the SSRS Web Server and implemented user security and roles at both the parent and report levels. Additionally, established SSRS Report Email Subscriptions, incorporating data-driven and time-driven subscription methods. |
