VAL VOLOVIK

** ********** **, ******, ** ***** 203-***-****

ac9xkw@r.postjobfree.com

SUMMARY OF QUALIFICATIONS

Application Developer/Hands-on Manager with extensive experience in SAS/R Programming and Statistical Analysis as well as in Data Bases and Data Warehousing design and development, with 20-year experience in SAS/R and overall 30-year experience in Databases and Systems Management and Design.

COMPUTER SKILLS

Language: Python, SAS/Base, SAS/Macros, SAS/Stat, SAS/GRID, SAS/CDI, SAS/EG, SAS/Studio, SAS/Graph, SAS/ODS, SAS/SQL, SAS/DI Studio, SAS Data Quality, SAS/EBI, SAS Visual Analytics, Bash scripting, R, XML, HTML, Java, JavaScript, JSP, Java Servlets, ANSI SQL, HQL, PostgreSQL, C, C++, Object Oriented Design, Cobol, Visual Basic.

Operating System: LINUX, Cloud Computing (AWS), UNIX, Windows Client/Server, OS/MVS.

Big Data Systems: BigInsight Hadoop, Cloudera Hadoop, HDFS, Oozie Workflow Engine, JSON and AVRO formats.

Data Base Management Systems: Redshift, Netezza, SQL Server, Oracle, MySQL, Teradata, DB2, MS Access, IDMS, IMS.

Software and Platform Development Tools: Amazon Web Services (AWS), Looker, SQL Workbench/J, Information Builder (IB), Tableau, Toad SQL Tool, SQL Developer Tool, Eclipse Web Tools, Aginity Workbench.

PROFESSIONAL EXPERIENCE

Star Group Stamford, CT June 2018 – current

Data Architect, Consultant

Designed, developed and optimized BI Analytics Solutions using Amazon Web Services (AWS) cloud computing. Participated in the following projects:

Design and building of BI Solutions Redshift Data Warehouse with several schemas and tables either replicated from SQL Server transactional databases or created using SQL query scripts for the use of BI Analytics and Looker based Reporting System;

Design and development of Redshift Databases Metadata Tables DDL History backup application with storing all aspects of tables DDL: table columns attributes, constraints, table distribution style and key, sort keys, primary keys, views definitions. The Redshift Metadata History was stored by Database, Schema, Table, and View for 30 days with ability to create restoration script and restore Table’s Metadata for any stored day;

Design and development of application to copy set of tables to different Redshift schema with preservation of column constraints, and primary keys with changing/adding distribution style and key, and sort keys (Redshift allows you to add distribution style and key, and sort keys only without constraints and primary keys preservation);

Design and development of workflow solutions for batch processing of SQL scripts on AWS EC2 instances using Python, Bash scripting, SQL scripting;

Design and development DMS (Database Migration Services) Monitoring Application for automatic checking of DMS workflow results that run overnight and submitting DMS workflow up to 3 (Application default) times if DMS tables replication failed with sending e-mails of DMS results for promptly reaction in case if DMS tables replication still failed.

The Monitoring Application reduced DMS table replication failures to 1 in 2 months. The DMS Monitoring Application used AWS DMS and SES (for e-mail sending) services (such DMS monitoring is not available in AWS as out of the shelf solution);

Optimization of Redshift SQL scripts with increasing SQL run speed by 10-50 times;

Design and development of Redshift Metadata system reports covering all aspects of Data Warehouse databases, schemas, tables, table, columns, table data distribution, etc.;

Design and development dynamic schema tables’ backup into back schema on Redshift with automatic writing SQL backup script based on the list of tables taken from Redshift Metadata using Python, Bash scripts, SQL scripts;

Design and development Redshift Database schema tables DDL and view scripts backup history for 30 days with possible restoring Redshift table DDL or view script if error had been made in changing table DDL or changing, accidental deleting of view script. The development used SQL Metadata scripts to extract all aspects of table DDL information (Redshift SQL ran using psql utility in Bash script), Bash scripts took those information, parsed it and converted to Insert SQL script to insert table DDL information into Metadata tables DDL History table for the run date (such solution is not available in AWS as out of the shelf solution).

Destiny Corp Rocky Hill, CT October 2015 – May 2018

Senior Consultant

Participated in Big Data System development and conversion from the Cloudera Hadoop to the Big Insight Hadoop for the major financial company. The system included reading and conversion input data (Oracle Data Warehouse tables, delimited files) to the JSON format using Oozie Workflow Web Console, Python programs for converting delimited files to JSON, transferring JSON files to AVRO format, Load AVRO files into HDFS, Load Hadoop files to Hive and querying files using HQL scripts, output data from Hadoop and loading it to the Netezza DB, reviewing and updating system’s workflows Bash scripts, BI reporting and model execution using R.

Designed and developed Logging/Monitoring Application for SAS GRID Workload with parsing nmon and processes data and creating SAS reports and drilldown graphs for CPU, Memory and I/O utilization of UNIX production servers.

Designed and developed Stress Test Application for SAS GRID Environment with stress test strategy Metadata, stress test scripts generation using Metadata, stress test results reports and graphs.

Managed project for design and development of Experian Netezza based Applications with definition of Data Model, development and testing of ETL, SQL scripts, Bash scripts calling SQL scripts for parallel processing. The Application was redesigned and converted from SAS based application into Netezza SQL scripts. The project utilized SAS Base, SAS Macros, SAS PROC SQL, ODS, Postgresql, UDF functions, nzsql, nzload, Aginity Workbench, analysis of Query Execution Plans, Bash scripting.

Developed ETL Oracle Data Warehouse tables to Apache Hadoop Data Lake, wrote MapReduce for Big Data file aggregation using Apache Spark Hadoop, Java.

Redesigned and developed SAS Applications with Netezza Database to the Netezza Applications reducing run time of Applications from 40 hours to 20 sec using Postgresql, nzsql, Aginity Workbench, SAS.

Developed R Analysis Application with Netezza Database using Postgresql, nzsql, Aginity Workbench, R.

Citizens Bank Bridgeport, CT March 2015 – September 2015

Senior Consultant

Developed BI reporting applications for the Credit Card Analytics, BI division and CCAR using T-SQL, SQL Server environment (SQL Management Studio and Toad) with query connections by ODBC to Excel or SAS;

Developed the Decision Tree System for bank’s Marketing campaigns using Data Sources of company’s Data Warehouse, querying Oracle based tables using PROC SQL and SQL Pass-Through facility, and creating the set of SAS macros for each marketing offer according to decision tree algorithms.

Destiny Corp Rocky Hill, CT June 2014 – February 2015

Senior Consultant

As a part of SAS Institute consulting group helped the large Bio-pharmaceutical company (Celgene Corp.) to migrate the Clinical Data Integration (CDI) and Clinical Studies (including SDTM and ADaM datasets, and TLGs) systems from SAS 9.2 on Windows Servers to SAS/GRID on Linux Servers with SAS 9.4. Rewrote several clinical studies macros and processes from SAS 9.2 on Windows to SAS 9.4 on Linux using SAS/GRID, SAS/EG, SAS/Studio, SAS/DI Studio, SAS Management Console, etc.;

Performed Installation and Operational Qualifications(IQ and OQ) of SAS 9.4 Foundation, SAS/GRID, SAS Studio, SAS EG and SAS CDI on Linux platform;

Redesigned and redeveloped SAS long running application to the Netezza SQL Application reducing the application’s run time from 14 hours to 30 minutes as the POC project for the major Data Integration company using SAS 9.4, Netezza SQL and PLSQL, Aginity Front End ;

Participated in Migration of Business Intelligence and Analytics Systems of the Nationwide Bank from SAS 9.2 Windows Servers to SAS 9.4 UNIX AIX Operating System utilizing SAS 9.4 Base, SAS/Macros, SAS/DI Studio, SAS X commands, Windows and Unix commands;

Data Quality Analysis of complex Data Sources, Reporting with dashboards and drill down capabilities using R, SAS DataFlux Studio, SAS Data Quality, SAS Visual Analytics, Tableau.

Alliant Data Brewster, NY June 2011 – May 2014

Senior Application Analyst

Designed and developed Profile Analysis and Reporting System on LINUX platform. The Profile Analysis and Reporting System include the following components:

Profile analysis and reporting metadata;

Calculation and aggregation of profile analysis variables for benchmark and client files;

RTF reports generation using SAS Graphs and SAS Visual Analytics

Developed Statistical Analysis and Response Modeling for Analytical Data base contributors (logistic regression).

Created online maintenance and edit of Client Metadata tables in production database using Java, JavaScript, JSP, HTML, MySQL.

Designed and developed and added to Analytical database Last frequency and recency transaction variable aggregation and generation by client and major levels (more than 10,000 variables) utilizing designed variable naming convention, SAS Macros, SAS Base.

Developed online scoring client usage reports from HTML scoring results using Java, HTML, MySQL.

Converted database extract store procedure processes and scripts from Oracle to MySQL database using Oracle PL/SQL, MySQL Store Procedures, Bash scripts.

Designed ETL History database, developed transformed variable measurements aggregation and QC Reporting System using SAS Macros, SAS Base, SAS/DI Studio, SAS DataFlux Studio, SAS SQL, Syncsort.

Converted e-mail and phone editing procedures from Oracle PL/SQL to SAS Perl Regular expressions.

Developed Real Time Scoring model modules converting SAS scoring programs to Java scoring classes.

Destiny Corp Rocky Hill, CT April 2011 – August 2011

Senior Consultant

Teamed up with the principal Netezza Developer in redesign of Compliances proprietary SAS applications to Netezza Applications for the Citigroup. The project design included the following steps:

Analyzing Compliances proprietary SAS applications and recreating steps of an existing main algorithm.

Redesign Applications data with Netezza instead of SAS tables and creating new main application algorithm.

Developed BI queries and reports for the CCAR using Netezza, SQL, SAS Base, SAS Macros, SQL and other SAS Procs, AWS Redshift load and querying.

Redesigned SAS Applications to Netteza platform substituting SAS Macro and Data Step processing with Netezza Store Procedures. The project design and development included the following steps:

Creating Flowcharts, Dataflow and Specifications of existing Applications from SAS source code.

Analyzing, creating proposals and presenting them to the client for redesigned Applications.

Designing and testing new Applications using Netteza Store Procedure, Netezza statistical functions in i-class, Netezza tables Loader and Extractor, Aginity Development Software for Store Procedures design and testing.

Comparing results from old and new Applications and presenting them to the client.

Affinion Group Stamford, CT November 1996 – January 2011

Manager

Designed and developed Regression Model Scoring System on LINUX platform. The scoring system has following workflow:

Daily ETL transformation job extracts data and metadata file-pairs from Mainframe and Linux Oracle Data Warehouse using PL/SQL, SQL, SAS and SyncSort via SFTP with file encryption/decryption and transforms and loads them into LINUX using SAS application that verifies data files’ integrity against metadata. Crontab is used for job scheduling.

SAS/Macros are executed against regression model variables to generate a SAS based scoring application according to predefined application framework and scoring templates. This mechanism allowed for generation of scoring application in 5-10 minutes instead of 16 hours. The scoring application generates macros that aggregate transactional data into promotional, membership, billing analytical data marts for use as historical variables in regression model. It also performs ETL transformation and stores files and scoring processing results in scoring metadata tables. Finally it stores scoring model’s statistics in historical model statistic tables.

Designed and managed development of Sample Preparation System on LINUX platform with various samples using a number tables and sample selection techniques.

The system selects samples from the campaign using simple, stratified, reduced sampling or oversampling techniques, creates promotional, membership and billing analytical data marts from historical transactional data, merges analytical data marts and 3rd party Data sources with selected sample for statistical analysis and regression model building and finally creating sample metadata tables, and QA and exploratory data analysis reports.

Developed Membership cancels analysis and as a result created the different categories of marketing suppression criteria.

Designed and developed modules for logistic regression modeling and response models.

Designed and developed Campaign Management and Suppression Database and Reporting System on LINUX.

The systems stores campaign and suppression records (records excluded from campaigns by company business rules) files into database tables and creates summary report linked to campaign reports by URL links.

Participated in installation of SAS/EBI on LINUX platform.

Designed Campaign Management Tracking Reporting System using SAS/EBI and BI Web Report Studio.

Designed and implemented Proof of Concept project to compare performance of company’s core analytical applications on different platforms such as SAS/Mainframe, SAS/LINUX, and SAS/LINUX/ Netezza. As part of this project redesigned applications for SAS/LINUX and SAS/LINUX/ Netezza platforms by using SAS Proc SQL and path through techniques for Netezza instead of Data step Merge on Mainframe. Moved files into SAS and Netezza Data Base using SAS Cport/Cimport and Netezza Loader.

The Results of the POC showed that using SAS/LINUX improved performance by 2-10 times over SAS/Mainframe and that using SAS/LINUX/Netezza outperformed SAS/LINUX but not significantly enough to justify much larger hardware overhead.

As a result of the POC project above redesigned and with help of our development team implemented porting of the core analytical systems from the mainframe to the LINUX platform. This project was estimated at 8 million dollars by outside Consulting Company, but was implemented without any external cost.

Designed the analytical data mart from membership and usage database and created the Cancel and Usage membership analysis for one of the German banks (for company’s international division).

Designed a system that reduced the time required the set up of scoring application on Mainframe platform from 16 hours to 20 minutes.

The system generated the following application’s components:

Scoring program by applying scoring framework and scoring templates

10-20-step scoring JCL procedure for merging files and executing scoring model

Sort and merge parameters using in Syncsort sort/merge steps

Scoring JCL code with JCL parameters.

Created cancel and tenure statistical analysis for entire membership database.

Designed analytical data base used for various statistical analysis and profiling.

Designed analytical database for a major franchise. The database combined data warehouses of nine individual companies creating a single view of customer’s household across all these companies’ data.

Designed regression model scoring system using C and SAS.

Programming Department, CPS Stamford, CT February 1990 – October 1996

Senior Programmer/Analyst, Systems Analyst

Developed Windows based Life Reinsurance Processing System (LRPS) for a major insurance company using C++ and Object Oriented Design

Designed and developed Life Insurance Management System (LIMS) for a major insurance company with online and batch subsystems utilizing IDMS PC, ADSO, COBOL

Participated in development of LRPS on mainframe with online and batch subsystems utilizing IDMS, ADSO, CICS, COBOL

Developed LIMS on mainframe platform with online and batch subsystems utilizing IDMS, ADSO, CICS, COBOL

PUBLICATIONS

Migration from Mainframe to LINUX: Leading but still Bleeding Edge NESUG 2009

Fancy arrays: Fun and Useful for Analytical Data Marts NESUG 2010

Data Validation and Transformation in ETL Processing with Help of Perl

Regular Expressions in SAS NESUG 2012

EDUCATION

AWS Technical Professional Online Certificate

IB Reporting Essentials using App Studio Certificate

IB Building Info Apps using App Studio’s HTML Canvas Certificate

IB Metadata Essentials using App Studio Certificate

IBM Certified Specialist – IBM SPSS Data Analysis Certificate

IBM Certified Specialist – PureData System for Analytics v7.0 Certificate

IBM Certified Specialist – Information Management DB2 v10.0 Certificate

SAS BI (Business Intelligence) Norwalk, CT Certificate

SAS Proc REPORT New York, NY Certificate

XML Primer New York, NY Certificate

SAS Macros New York, NY Certificate

MS in Mathematics and Computer Science Odessa State University

BS in Mathematics Odessa State University

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