OBJECTIVE:

• Senior BI Developer/Big Data Engineer/BI Architect/Data Architect

SUMMARY:

• Ph.D with over 11 years’ experience in data warehousing and relational database design and development using a wide variety of Data Modeling, BI tools and technologies including Toad Data Modeler, Ervin and Confidential Stacks (SSIS, SSAS, SSRS, Data Mining, PowBI, Tableau). Involvement in all SDLC of BI Solution development process, from database design, application architecture, coding to database development and performance tuning.
• Professional experience with cloud computing and Hadoop development to load, query and analyze structured and unstructured data: Window Azure setup and admin, HDInsight clustering and HaaS (Hadoop as a Service) development with Azure Data Factory, Polybase, Sqoop, Hive,Impala,Pig, Oozie,Spark.
• Professional Experience on high - performance data integration solutions- Microsoft SQL Server Integration Service (SSIS), including extraction, transformation, and load (ETL) data from VLDB SQL Server, Oracle, SAP, cubes and FTP, flat files, SharePoint lists etc. to data warehousing and relational databases.
• Professional experience with T-SQL for SQL Server 2005/2008//2012/2014 , C#, VBA, MDX, DAX in SQL query design, SSIS package development, building SSAS Cubes and creating SSRS reports.
• Extensive experience on Microsoft SQL server Analysis Service (SSAS), including building and performance tuning the multidimensional and tabular cubes and Data Mining, Machine Learning for predictive analytics.
• Extensive experience with reporting tools SSRS, Crystal Reports, Pivot table and data visualization tools PowerBI, Tableau.
• Involved in the whole process of machine learning project from requirement collection, data preparation, featuring, building the model, evaluating the model: Classification, Clustering, Decision Trees, Random Forest, Logistic Regression, Neural Network, Naive Bayers, etc. algorithms and deploy the model with languages SQL, R, Python, Scala and Spark in Hadoop Ecosystem.
• Excellent communication skills and a self-learner willing and able to quickly acquire new skills.

COMPUTER SKILLS

Database: SQL Server 2005/2008/2012/2014/2106 , Oracle 10g/11g, SQL developer, Toad (Toad for SQL server, Erwin,Toad Data Modeler), Microsoft Azure, HDInsight, Cloudera, Epic Clarity, Hortonworks/Hadoop, HBase, NoSQL,, BIDS Helper, Access 2007/2010,GreenSQL

Statistical and Machine learning Packages: Spyder, Pycharm RStudio, Octave, GraphPad Prism, Azure Machine Learning, Jupyter Notebook, Zeppelin Notebook

Reporting: SSRS, Crystal Report 2008, Power BI, PowerView, PowerPivot, PowerQuery, PowerMap, Spotfire,Epic Reporting Workbench, Tableau

Language: SQL, T-SQL, PL/SQL, C#, Visual Basic, Unix, PowerShell, MDX, Python,Hive, Pig,Sqoop,Spark, R, SparkR Autosys job scheduling

MS Software: Microsoft Visual Studio 2010/2013, Microsoft Team Foundation Server 2010, Microsoft SharePoint 2007/2010, Word, Excel, PowerPoint, Access.

EXPERIENCE:

Confidential, Charlotte, NC

Application Programmer V

Responsibilities:

• SSAS cube Processing Performance Tuning: Different technologies were used to tuning cube processing performance from different perspective: 1) SQL Server data warehouse as the data source of the cubes: Change the recovery mode to simple from full; create partitions for the fact tables; create different file groups for dimension and fact tables; Create Column Store indexes for the fact tables; tuning the query syntax etc. 2) SSAS server and cube schema tuning: Enhance the configuration of the SSAS server, like CoordinatorExecutionMode; BufferMemoryLimit etc.; materialized named queries and views in the DSV; 3) Tuning cube processing in SSIS packages: Changed the dimensions processing from ProcessUpdate to ProcessAdd; Parallel processing(MaxDOP) and incremental loading the cubes; used ProcessData and ProcessIndex instead of ProcessFull in partitions processing etc. All 3 cubes processing time improved spectacularly after these changes: from 5 hours to 20 mins; from 3 hours to 10 mins and from 6 hours to 10 mins.
• Migrating the SQL servers to Cloud Hadoop platform of the company (HAAS): Sqoop, WinSCP, pscp etc. were used to transfer unstructured and structured data to the HAAS including flat files, Excel files and SQL Servers. Using Hive, Impala, Spark and Python to transform and load the data in HDFS system. With Autosys, using Job Information Language (JIL) for definition and control of jobs on the Edge Node of the HAAS. As the code repository tool, Bitbucket was used to store, push and branch the code as it proceeds through the development lifecycle. Different interface, like Beeline, Hue and TOAD were used in the Hadoop development.
• Python application developed to automatically modify XML file, XSL files: To present the MDX scripts in graphic format to document the SSAS cubes, different packages, modules, functions were used in the application: Numpy, Pandas, ElementTree, re, os etc. for SSAS documentation purpose.

Environment: MS SQL Server 2016/2012/2008 (SSMS), Analysis Service(SSAS), HDFS, Hive, Pig, Sqoop, Hue, Spark, Spyder, Python, C#, MDX, XMLA. XSL,HTML,T-SQL, Jupyter, TOAD,Visual Studio 2010/2012, Autosys,Bitbucket, BIDS Helper, Integration Services (SSIS), Reporting Service(SSRS),Net, Pivot table, Excel

Confidential, Houston TX

Cloud/ Business Intelligence Architect

Responsibilities:

• Set up Azure data warehouse, Virtual Machine, Storage accounts to load data from different data sources to the data warehouse with Polybase and Star Schema is designed and built up in the Azure data warehouse to feed the machine learning data model.
• IoT Hub, stream analytics were set up to query data from the C# simulators of the sensors and load data to the Azure data warehouse.
• Build the predicative model in Azure Machine learning studio. Set up Machine learning workspace and machine learning web service plan in Microsoft Azure, Dimensionality Reduction (Principle Components Analysis and Exploratory factor analysis) in feature engineering.
• Built PowerBI reports to present the data from the predicative model and the data from IoT Hub.
• Configured and implemented Azure Data Factory to coordinate the data flow of this project.

Environment: Window Azure,Windows Azure Machine Learning Studio, Azure Data Factory, Polybase, IoT Hub, Stream analytics, Storage account, Virtual machine, Azure Data Warehouse, Azure Analysis Service. TFS, Integration Services (SSIS), Analysis Services(SSAS), RStudio, T-SQL, C#, MDX,SQL Server 2016, PowerBI,Excel.

Confidential, Winston Salem, NC

Business Intelligence Advisor

Responsibilities:

• Developed and Performance Tuning SSAS cubes: Different technologies were used in the developing and tuning process of the cubes: Data Type conversion, Creating partitions, aggregations and perspectives based on the user query patterns, naturalizing parent-child hierarchy(BIDS Helper), configuring measures and attributes properties, rewriting named sets and calculate members MDX scripts, Creating various hierarchies on role playing dimensions and creating specific names on different levels of the hierarchies etc. The query time from pivot table to the cube decreased from 20 mins to less than 10 seconds after the changes were promoted.
• SSIS packages designed to load data to the data warehouse and dynamically process the cube and execute the SSRS reports: Based on the different business requirement, the cubes were processed dynamically through the SSIS packages: Incremental or full processing the cubes. When incremental is needed. Process Update the dimensions and Process Full the partitions: VBA scripts, ASSP (Analysis Service Stored procedures) were used to get the information from the cube; delete unused partitions, create XMLA,VBA scripts to build and process new partitions, synch the build servers to query servers etc. RSS file and Script task were used in the SSIS package to dynamically execute the SSRS reports based on different parameter, format and target folder requirement.
• Lead the company efforts to migrate the company SSIS packages from SQL 2005, 2008 to SQL 2014: More than 400 SSIS packages need to be migrated to 2014 SSIS Server. Set up designing standards based on the up-to-date best practice of SSIS package designing to the packages which are developed at different time, with different version, by different developers. Standardized logging and configuration methods, configuration file and batch files were applied to make the migration efforts easier in the future. Schedule the jobs with CA workload automation(Autosys).
• SQL Server 2014 (Column-Store indexes) performance tuning: Column Store index maintenance plan created for the team to query the fragmentation information of the CCIs and reorganize or rebuild the CCIs based on the fragmentation percentage and business requirement. CCIs and indexed view were created to improve the Data Loading and Cube processing performance.

Environment: MS SQL Server 2014/2012/2008/2005 (SSMS), Visual Studio 2012/2013, .Net, TFS, Oracle 11g, SQL Developer 8.0, SAP, Toad Data Modeler, BIDS Helper, Integration Services (SSIS), Analysis Services(SSAS), Reporting Services (SSRS), T-SQL, SQL Server 2016 in Window Azure, PowerBI, Tableau,Excel.

Confidential, Greensboro, NC

Business Intelligence Consultant

Responsibilities:

• Different Business Rules were applied in these packages to meet different business requirements: Complex Script task written in C# language was used to apply different business rules to the staging table to check the data quality of the data source. Such as Empty Value Rule, Date Out of Range and Value Out of Range, Expected and Actual Percentage Rule etc. The function of this script task including: different methods were used to get data from the data source and the database like DataTable class, stored procedures, object variables etc; and apply complicate business logic to transform the data, meet the requirement of different business rule, log and audit the execution result into log and audit tables, generate email notification messages etc.
• Designed SSIS package to load the patient information into and extract data from CTD( CaseTrakker Dynamo) EMR system using SSRS and Tableu
• Designed SSIS package to import the patient information into the CTD system, create the notification message for the disease manager after the patient is loaded into the system, so the disease manager could process the case instantly. Created complex stored procedures in the package to extract data from CTD system to build various report for the management based on the different business requirement, such as Daily Patient Status report, Daily Shipment Report, Exception Report, Monthly Patient Case Report etc.
• Developed and Maintained Database Projects in the Visual Studio 2010 and 2012. Visual Source Safe (VSS), Team Foundation Server (TFS), and Visual Studio (VS) were used to develop the database project in a collaborative software development environment. Reverse engineering the current databases into the Visual Studio 2010 and 2012. Configure the different environment (such as local, development, UAT and production etc) for the database solution and database projects. Deploy any changes to the database project objects (tables, views, stored procedures, functions etc) to different environment databases after the changes are successfully built or gated check-in.

Environment: MS SQL Server 2014/2012/20 (SSMS), Visual Studio 2010/2012, TFS, VSS, Reporting Services (SSRS), Integration Services (SSIS), T-SQL,BI,Window Azure,PowerBI, Tableau,.Net, Excel, HDInsight, HDFS, Hive, Sqoop, Spark.

Confidential

Business Intelligence Architect

Responsibilities:

• Lead the Data Warehouse Project of the company: Evaluated the structure and business logic of relational databases. Regular communication with the business owner and developer to collect the business requirement and make the team to understand business intelligence workflows and ensure that the data models and query engines support those data and workflows. Developed a flexible, extensible and sustainable dimensional data model for the company. Various query building techniques and best practices of Star schemas, Snowflake schemas, multidimensional cubes, cleansing, normalization/denormalization, data mining, ETL and reporting performance etc. were taken into account in the logic and physical data modeling of the project. More dimensions from external data source were identified to make the function of the data warehouse more powerful.
• Designing robust and complex SSIS packages for the data warehouse project: Designed complex SSIS packages to load data from various sources to the data warehouse: flat file, excel file, FTP server of our client and other relational databases. Various SQL techniques (stored procedures, scalar and table value functions, views, triggers, cursors and complex T-SQL) and SSIS tasks were used in these packages: For Loop container, For Each Loop container, SQL Execute task, SQL Command, Script task, look up, and conditional split, file system task and send mail task etc. Robust audit and notification functions were designed in the packages: Metadata tables were created to log the activity of the packages, errors and change of the variable. Various techniques such as CDC, SCD and Hashbytes were used to capture the change of the data and execute incremental loading of the dimension tables. After the execution, the packages will send out successful or failure email alerts to users and developers. The jobs were set up in the SQL agent to execute the packages regularly based on the business requirement.
• Building the Cubes(SSAS multidimensional and tabular) and Creating the Reports (SSRS,Tableau): SSAS: created data source/data source view/cube with measure and dimensions, configured attributes of dimension table with hierarchy relationships, added new measure groups and dimensions, modified cube and dimensions, calculated new measures. SSRS: Built reports from Analysis Services cube using MDX query designer, configured report server and deployed reports on web servers, created data-driven subscription and Report Service execution logging. User-specific dynamic report was created to make the data secure. Tableau: Various ad-hoc dashboard and story reports are created from different data sources with or without data blending. Row-level calculation, aggregates calculations and table calculations (difference, percentage difference and running total, rank,etc), Hierarchy and cascading filters were used in these reports.
• Set up and administered Windows Azure. Created and deployed SQL Server database to Windows Azure from Visual Studio, Provisioned HDInsight Cluster(Hortonworks/Hadoop platform), connected to HDInsight, loaded, processed and queried data using Pig, Hive. Oozie.Transferred data between HDInsight and databases using Sqoop.
• Created models, entities and attributes in the Master Data Service (MDS):defined business rules, and created subscription views as the data source of SSIS package in dimension table loading. Managed model versioning.

Environment: MS SQL Server 2012/2008/2005/2000 (SSMS), Window Azure, HDFS, Hive, Pig, Sqoop, Hue, Spark, Visual Studio 2010/2012, TFS, Toad Data Modeler, BI xPress, DBA xPress, Doc xPress, BIDS Helper,Reporting Services (SSRS), Analysis Service(SSAS), Integration Services (SSIS), T-SQL, Spotfire,.Net, Excel.

Confidential, Charlotte, NC

Application Developer V

Responsibilities:

• Designing and maintenance complex SSIS packages: Designed, redesigned and provided technical support to complex SSIS packages to load data from various sources: complex Excel template, super large Excel files, SharePoint lists and other databases. These packages process a few hundred files automatically each day and load the extracted data to different tables, recognize and log the activity of the package and errors to metadata tables. After the execution, it sends out successful or failure email alerts to users.
• Development of New Function to the Application: Developed new function to the current SSIS package by writing complex stored procedure more than one thousand rows to make the aggregated data input automatically based on complex business requirement. Before the new function, only less than 50% of detailed data was aggregated and posted, after the new function was added to the package, more than 97% detailed data was summed and posted automatically by the package, only a little of them need to be manually typed in.
• Designing and Technical Support to Database Driven Application: helped to design and provide technical support to Excel - based database driven application and ASP.net based web application to help the business users to input and change the different test attributes information.

Confidential, Winston Salem, NC

Sr. BI Developer/BI Architect

Responsibilities:

• SSIS: Successfully loaded the data from the experiments of LTP (long term potentiation) on mice hippocampus, molecular biology data and medical records to SQL Server2008/2012. Created ETL packages using SQL Server 2005/2008/2012 SSIS Designer to extract data from relational databases (SQL server, Oracle ), from Epic EHR system (Epic Clarity databases), different types of flat file (XML, CSV, pipe - delimited, fixed width), cleaned up the data using Data Quality Service(DQS), Master Data Service(MDS)and transformed the data using various dataflow components (i.e.
• lookup, union, merge, merge join, conditional splits, derived column, script component, etc.), and inserted the cleaned and transformed data into fact table, loaded different types of dimension and fact tables into data warehouse, deployed SSIS packages and solutions into SSMS using SQL Server Business Intelligence Development Studio (BIDS) and SQL Server Data Tools(SSDT), configured the SSIS solutions (packages level or projects level) to execute in test and production environments. Conducted logging and custom logging to handle the errors created when executing the ETL packages.
• Defined jobs for the packages and other tasks in SQL server management studio, scheduled the jobs to run at designated time and report the success or failure of the jobs to the operator. SSAS: Building the cube: Developed projects using SQL Server 2008/2012 OLAP tools, deployed KPIs on SSRS and created different metrics. Data Mining: Created Data Mining solutions for predictive analytics in BIDS (2008) and SSTD (2012). Data Mining Models were created from relational databases and cubes using Data Mining Extensions (DMX) and Data Mining Wizard.
• Different Data Mining Algorithm including Na ve Bayes, Neural Networks, Decision Trees, Time Series and Clustering were used to create the Data Mining Models. Deployed the models to SSAS instance, trained the models, queried the models using Multidimensional Expressins (MDX) and applied Data Mining Prediction in SSIS and SQL Server data mining add-in for Excel. SSRS and Crystal Report: Generated variety of business reports using SQL Server 2008/2012 SSRS and Crystal Report 2008 including tabular report, matrix report, parameter report, cascading parameter report, dynamic columns from parameter or action report, dynamic images report, user-specific dynamic report, sub-report, dashboard with charts and drill down function, created report snapshots and caching.
• Whole lifecycle of Relational Database and Data Warehouse Design: Designed and build data warehouses(star schema, snowflake schema and hybrid model) and relational database of medical records and biological research data, went through the whole lifecycle of data warehousing from collecting business requirement, conceptual, logic, physical data modeling, to data profiling, data cleansing, ETL data staging, metadata management, data analysis and creating various business reports using Microsoft SQL server and Business Intelligence tools.
• Varies dimension tables were created in the projects, including role-playing dimensions, minidimensions, fact dimensions, multivalued dimensions, etc.
• Data Warehouse Maintenance: Performed data warehouse maintenance including backup and restoration; logging shipping; deployment of data warehouse to Windows Azure; SQL performance tuning using Dynamic Management Views(DMV), SQL profiler, SQL server tuning advisor and SQL execution plan; creation and defragmentation indexes; handling large tables with table partitioning and partition switch technology. Confidential Winston Salem, NC Data Analyst
• Set up a new patch-clamp lab successfully and independently, conducted project scheduling, experimental instruments designing, data collecting, data analyzing and data presenting.
• Successfully loaded the data from the AOB (accessory olfactory bulb) calcium current of mice from Clamp10.0, Clampfit 10.0 to Access 2003 and SQL 2005.
• Analyze and present the complicated data from AOB calcium current (different time point, different chemicals, different stimulus protocol, different age mice, etc.) using SQL 2005, MS Access 2003, MS Excel 2003 and PowerPoint 2003.