SUMMARY

• Design of Data warehouse and data marts with Star schemas and Snowflake architecture using Kimball Dimensional Modelling
• Work with the Cloud Architect and Cloud Business Services unit to implement the Analytics Platform as a hybrid cloud solution using Azure.
• In depth knowledge of IaaS, PaaS & SaaS services in the Microsoft Azure cloud platform, specifically Azure Data Lake, SQL DB, AAS and ADF.
• Advanced understanding of distributed systems architecture in Azure
• Work alongside customers to build data management platforms using Azure Technologies like Data factory, Blob, Azure Data Lake and other cloud services.
• Strong knowledge and proven experience of Enterprise Application Integration and Architecture patterns
• ETL/ELT/SSIS/Data Factory Hands - on experience using Business Intelligence technologies to implement data integration, data warehousing, analytics, reporting and dashboards.
• Strong understanding of Application Lifecycle Management best practices for Development, Testing, CI/CD, Monitoring
• Analytical and Operational reporting
• Business and Database Analysis, Enterprise (OLTP) and Dimensional (OLAP) Data Modeling, ODS
• Integration Cloud applications with traditional Data Warehouse Applications
• ETL Workflow Design, Development and Performance tuning.
• Scheduling, load balancing, processing high volumes, disaster recovery, data archiving, backup and restore policies and solutions.

TECHNICAL SKILLS

Databases: AZURE Synapse Analytics (AZURE SQL DW), SQL/Server 2019, 2016/2012/2008/2005/2000 , RedShift, Sybase, Oracle 11g, Snowflake, DB2, MySQL, Teradata, Hadoop/Hive, SAAS

Systems AZURE, Windows, UNIX, AWS, Linux,:

Languages: PL/SQL, T-SQL, Visual Basic, C#, Power/Shell Scripting

Internet: JavaScript, XML, JSON, HTML, ADO, OLE-DB, JDBC, MSMQ

Data Modeling: ERWIN, ER/Studio, MDM, SSAS Tabular and Multidimensional, Power Query

ETL/ELT: AZURE Data Factory, SSIS, Stored Procs, Triggers, AWS Pipeline, AWS Migration tool, Data Bricks

Cloud: AZURE Storage, ADSL (BLOB and Data Lake), SQL Data Warehouse, RedShift, S3, EC2, RDS, PostgreSQL, MySQL, IoT Hub

Big Data: HDFS, HIVE, Hadoop, Data Lake Analytics, RESTFULL APIs

BI Platform: SSAS, SSIS, Tableau, Power BI

Administration: SQL Server, ORACLE, AZURE, Redshift, Import/Export, AutoSyS, TIDAL, Control M

Data Visualization: POWER BI, Tableau, SSRS, Excel, Crystal Reports

Miscellaneous: Agile, Azure DevOps, CI/CD, JIRA, MS Office, GIT, GITHUB, Visio, PowerPoint, Share Point, TFS

PROFESSIONAL EXPERIENCE

Confidential

Senior Data Warehouse and ETL Architect/Business Intelligence Engineer

Responsibilities:

• Designed and implemented Vendor Transportation data warehouse in hybrid Business Intelligence environment lifecycle. The business needs consisted multiple subject areas including, Compliance, Finance/Cost, Reporting.
• Designed an enterprise data model (EDM) for effective data management, data governance and to identify omissions by organizing the data by subject area rather than by application.
• Azure complete stack lead - data factory, data lakes, AAS, Azure DW
• Integrated data provided a “single version of the truth” to allow the organization to minimize data redundancy, disparity, errors, to improve overall performance for the performance of data consistency, accuracy, validity and other data quality dimensions to enable business insight.
• Designed DW SSIS/Data Factory ETL/ELT to check for general errors, support auditing of row counts, financial amounts, and other metrics.
• Deployed SSIS packages in the cloud by utilizing the Integration Runtimes feature for Azure Data Factory (Lift & Shift).
• Used the Azure PowerShell module to create and to manage Azure resources and to run SSIS packages.
• Designed and wrote the entire ETL/ELT (SSIS/ADF/T-SQL) process to support Data Warehouse with complex dependencies in hybrid Business Intelligence environment (Azure & SQL Server).
• CI/CD lifecycle for Azure data factory, configured with Repos GitHub for production and staging deployments .
• Created Data warehouse analytical Reporting Visualizations using Power BI dashboards, trendlines, donut chart, bubble Filters, Hierarchies, Data Blending, Parameters, PKIs.
• Designed data lineage to provide tracing capability from the source to target and to verify how data was transformed for the integrity of the downstream data.
• Designed and Developed operational reports (SSRS) and business intelligence reports using Tabular SSAS and Power BI for Vendor Transportation GPS system across multiple subject areas.
• Identified risks/issues with the solution design and contributed to solution architecture of BI/DW development work.
• Senior level understanding of warehousing architectures including ETL/ELT design, staging, transformations, source-to-target mapping rules, star-schemas, cubes, and history loading.
• Collaborated with IT Operations on defining load balancing, processing high volumes and large tables, clustering, mirroring, Always ON, disaster recovery, data archiving, backup and restore policies and solutions.
• Performed tuning of large databases, database partitioning, and SSIS ETL/Queries optimization.
• Audit and Reconciliation processes, Sandbox environments and ETL/ELT SSIS/ADF best practices.

Technology: SQL Server 2016, SSIS, ADF, SSAS, SSRS, Power BI, data pipelines in AZURE, Data lake

Confidential

Senior Data Warehouse Architect and ETL/Business Intelligence Engineer, Consultant

Responsibilities:

• For International Rescue Committee Company, enhanced and implemented a data management platform Award Portfolio Management Enterprise DW System, that handled gathering the data from multiple systems (Opportunity Tracking & Implementation System (OTIS), Budget versus Actual (VA) and etc.) then curated, integrated and activated the entire data to produce insights (involving data visualization and predictive modeling tools).
• Designed and wrote the entire ETL/ELT (SSIS/T-SQL) process to support Data Warehouse with complex dependencies in hybrid Business Intelligence environment.
• Created SSIS Packages to migrate data from local DW to Azure Cloud (Azure SQL Database), Azure Blob Storage.
• Used the Azure PowerShell module to create and to manage Azure resources and to run SSIS packages.
• Understand the functional design requirements for a cloud-based Data Management solution and design conceptual, logical, physical data models that can meet current and future business needs. Ensure designs
• Designed and Developed operational reports (SSRS) and business intelligence reports using Power BI for International Markets analysis from multiple sources to optimize efficient use of financial resources with globally distributed teams. Ability to work on complex projects with globally distributed teams and tight timelines.
• Worked with stakeholders, data scientists, developers, IT Operations, and DBA services to design and develop scalable enterprise databases and ETL/SSIS solutions.
• Create SSRS reports, matrix, Drilldown, Drill through, cascading Parameterized, OLAP cubes, Sub reports, charts, report parts, interactive sorting, deployment, subscriptions.
• Identified risks/issues with the solution design and contributed to solution architecture of BI/DW development work.
• Senior level understanding of warehousing architectures including ETL design, staging, transformations, delta/change data capture, star-schemas, cubes, and history loading.
• Collaborated with IT Operations on defining load balancing, processing large files and large tables, clustering, mirroring, disaster recovery, data archiving, and backup policies and solutions.
• Performed data analysis on source system data for documenting source to target mapping and transformation rules (SSIS).
• Performed tuning of large databases, database partitioning, and SSIS/AD/ETL/Queries optimization.
• Complex source-to-target mapping rules and techniques, Data Quality best practices and techniques.
• Worked in very large database environments, providing production support within different time zones.

Technology: SQL Server 2016, Oracle 11g, SSIS, ADF, SSAS, SSRS, Power BI, data pipelines in AZURE

Confidential

Senior Data Warehouse Architect and ETL/Business Intelligence Engineer, Consultant

Responsibilities:

• Designed Electronic Response Data warehouse in hybrid environment for storing and for reporting on Wealth Care Admin feedbacks for primaries and for dependents accounts. Built statistical reports using SSRS and (KPIs) to present Comparison Analysis, Variance Analysis, Pareto Analysis and Correlation Analysis.
• Supported the BI Information Architecture in developing and deploying BI/Data Integration solutions for the project team on premises and Azure cloud.
• Worked with stakeholders, data scientists, developers, IT Operations, and DBA services to design and develop scalable enterprise databases and ETL/ELT/ADF/SSIS solutions.
• Collaborated with IT Operations on defining load balancing, processing large files and large tables, clustering, data archiving, and backup policies and solutions.
• Performed data analysis on source system data for documenting source to target mapping and transformation rules.
• Performed tuning of large databases, database partitioning, and ETL/Query optimization.
• Designed and wrote the entire ETL/ELT/ADF/SSIS/T-SQL process to support Data Warehouse with complex dependencies including scheduler, SSAS cubes (Multidimensional and Tabular), SSRS reports, complex SSIS packages, multiple SQL stored procedures, functions (T-SQL) and triggers.
• Worked with the BI offshore team and business partners to validate rules regarding data integrity and data quality.
• Development analytical Tableau dashboards and Operational SSRS reports.
• Migrated SQL Data Warehouse on premises to Azure environment.

Technology: SQL Server, Oracle 11g, SSIS, ADF, SSAS, SSRS, data pipelines in AZURE, Data Lake, Tableau, Erwin

Confidential

Senior Data Warehouse Architect and ETL/Business Intelligence Engineer, Consultant

Responsibilities:

• For Hamilton Insurance Company lead, enhanced and implemented Policy/Claims Billing data warehouse in hybrid Business Intelligence environment lifecycle.
• Supported the daily monitoring/data integration/ETL process during mission critical times and guided with problem resolution
• Evaluate and plan DWH migrations to cloud.
• Collaborated with IT Operations on defining load balancing, processing large files and large tables, clustering, mirroring, disaster recovery, data archiving, and backup policies and solutions.
• Performed data analysis on source system data for documenting source to target mapping and transformation rules.
• Designed and implemented in SSIS ETL/ELT process to support various reporting tools in Claims System Data Warehouse (Star-Schema and Snowflake Schema).
• Prepared various test data to stress the system and to test anomalies
• Enhanced company's business intelligence platform, including KPIs, management reports, dashboards, operational reports, and ad-hoc analysis of data.
• Mapped the data from external structured and unstructured sources (Clarion door, Am Wins, Guide Wire, etc.) to ingest data to Quote Data Warehouse (Star schema).
• Performed tuning of large databases, database partitioning, and ETL/Query optimization.
• Participated in thought leadership and ongoing decisions regarding information architecture, data collection, data analysis methodology, and information distribution.
• Development analytical enterprise dashboards Power BI and Operational SSRS reports.
• SQL Server Data warehouse migration to Azure SQL Data Warehouse.
• Worked with business users and management to analyze, define, and document business requirements for data needs.
• Designed and wrote the entire ETL/ELT/ADF (SSIS/T-SQL) process to support near Real-Time Data Warehouse with complex dependencies including scheduler, SSAS cubes (Multidimensional and Tabular), SSRS reports, complex SSIS packages, multiple SQL stored procedures (T-SQL) and triggers.
• Used domain knowledge and business requirements to model subject areas and data attributes.
• Worked with the BI (Tableau) offshore team and business partners to validate rules regarding data integrity and data quality.
• Performed tuning of large databases, performance optimization (SQL Server), database partitioning, and ETL/Query optimization.

Technology: SQL Server, SSIS, ADF, SSAS, SSRS, AZURE, Data Lake Tableau, Erwin