SUMMARY:

• Designer, builder and manager of Big Data infrastructures
• A collaborative engineering professional with substantial experience designing and executing solutions for complex business problems involving large scale data warehousing, real - time analytics and reporting solutions.
• Known for using the right tools when and where they make sense and creating an intuitive architecture that helps organizations effectively analyze and process terabytes of structured and unstructured data.

COMPETENCY SYNOPSIS:

Data Warehousing: Proven history of building large-scale data processing systems and serving as an expert in data warehousing solutions while working with a variety of database technologies. Experience architecting highly scalable, distributed systems using different open source tools as well as designing and optimizing large, multi-terabyte data warehouses. Able to integrate state-of-the-art Big Data technologies into the overall architecture and lead a team of developers through the construction, testing and implementation phase.

Databases and Tools: MySQL, MS SQL Server, Oracle, DB2, NoSQL: HBase, SAP HANA, HDFS, MongoDB,, Vertica, Greenplum, Pentaho and Teradata.

Data Analysis: Consulted with business partners and made recommendations to improve the effectiveness of Big Data systems, descriptive analytics systems, and prescriptive analytics systems. Integrated new tools and developed technology frameworks/prototypes to accelerate the data integration process and empower the deployment of predictive analytics. Working knowledge of machine learning and/or predictive modeling.

Tools: Hive, Pig and Hadoop Streaming, MapReduce,Spark.

Data Transformation: Experience designing, reviewing, implementing and optimizing data transformation processes in the Hadoop and Informatica ecosystems. Able to consolidate, validate and cleanse data from a vast range of sources - from applications and databases to files and Web services.

Data Collection: Capable of extracting data from an existing database, Web sources or APIs. Experience designing and implementing fast and efficient data acquisition using Big Data processing techniques and tools.

PROFESSIONAL EXPERIENCE:

Confidential

Big Data Engg

Responsibilities:

• Designed a large data warehouse using star schema, flow-flake.
• Designed and developed Big Data analytics platform for processing customer viewing preferences using Scala, Hadoop, Spark and Hive .
• Integrated Hadoop into traditional ETL, accelerating the extraction, transformation, and loading of massive structured and unstructured data.
• Loaded the aggregate data into a Vertica for reporting, dash boarding and ad-hoc analyses, which revealed ways to lower operating costs and offset the rising cost of programming.
• Installed and configured Apache Hadoop, Spark and scala environment on the prototype server.
• Configured SQL database to store Spark metadata
• Created reports and dashboards using structured and unstructured data n different Tools like Tableau
• Created Schema, Tables, and T-SQL scripts to archive Vertica resource usage data (memory usage, CPU usage, storage usage, error messages, query requests, etc.) for trend analysi s
• Participated in mass deployments involving both updates to existing database objects as well as creation of new database objects.
• Involved in Rebalance ing of vertica cluster and Backup and Recovery
• Involved Resource Management, Memory Managemen t for the space on vertica server.
• Involved in building Datawarehouse on vertica and do the performance tuning on vertica tables
• Involved create the log on vertica to handle error logs.
• Generated Dashboards with Quick filters, Parameters and sets to handle views more efficiently.
• Generated context filters and data source filters while handling huge volume of data.
• Built dashboards for measures with forecast, trend line and reference lines
• Experience in creating different Visualizations using Bars, Lines and Pies, Maps, Scatter plots, Gantts, Bubbles, Histograms, Bullets, Heat maps and Highlight tables

Confidential, San Francisco

Big Data Engg

Responsibilities:

• Installed and configured Apache Hadoop, Vertica and Pig environment on the prototype server.
• Configured SQL database to store Spark metadata.
• Design data analysis platform for business using python, Hadoop and spark.
• Loaded unstructured data into Hadoop File System (HDFS). Big
• Created ETL jobs to load J SON data and server data into and i nto the Teradata using python
• Created Schema, Tables, and T-SQL scripts to archive Vertica resource usage data (memory usage, CPU usage, storage usage, error messages, query requests, etc.) for trend analysis
• Participated in mass deployments involving both updates to existing database objects as well as creation of new database objects.
• Involved in Rebalanceing of vertica cluster and Backup and Recovery
• Involved Resource Management, Memory Management for the space on vertica server.
• Involved in building Datawarehouse on vertica and do the performance tuning on vertica tables
• Involved create the log on vertica to handle error logs. .
• Created reports and dashboards using structured and unstructured data n different Tools like Tableau
• Generated Dashboards with Quick filters, Parameters and sets to handle views more efficiently.
• Generated context filters and data source filters while handling huge volume of data.
• Built dashboards for measures with forecast, trend line and reference lines
• Experience in creating different Visualizations using Bars, Lines and Pies, Maps, Scatter plots, Gantts, Bubbles, Histograms, Bullets, Heat maps and Highlight tables.

Confidential

Data Architect / Developer

Responsibilities:

• Gathered business requirements, definition and design of the data sourcing and data flows, data quality analysis, working in conjunction with the data warehouse architect on the development of logical data models.
• Used Erwin for data modeling.
• Created complex Stored Procedures , Triggers, Functions , Indexes, Tables, Views and other T-SQL code and SQL joins for applications.
• Implemented database standards and naming convention for the database objects. established data granularity standards, designed and built star and snowflake dimensional models
• Developed Informatica Packages to extract, transform and load (ETL) data into the data warehouse database from heterogeneous databases/data sources
• Designed Star Schema modeling creating Facts, Dimensions, Measures and Cubes . and optimized data connections, Data Extracts , Schedules for background tasks and Incremental Refresh for the weekly and monthly dashboard reports on Tableau Server.
• Used Excel Sheets , Flat files , CSV files to generate Tableau adhoc reports. Involved in creating calculated fields, mapping and hierarchies.
• Generated Context Filters and used performance actions while handling huge volume of data. Generated tableau dashboards for sales with forecast and Reference lines.
• Very proficient in working with large Databases in DB2, Oracle, Teradata and SQL Server.
• Strong understanding of Data warehouse concepts, ETL, Star Schema, Snowflake, physical and logical data models.
• Depth knowledge of Normalizations, Fact and Dimensional tables.
• Involved in creating Complex Stored Procedures , Triggers , Cursors , Tables and Views and other SQL joins and statements for reporting application development.
• Worked on building queries to retrieve data into Tableau from Oracle and developed SQL statements (ETL) for loading data into Target Schema.
• Excellent analytical and problem solving using Tableau and SQL debugging skills. Drive informed decisions by analyzing business and product performanc e

Confidential

Data Developer

Responsibilities:

• Gathered business requirements, definition and design of the data sourcing and data flows, data quality analysis, working in conjunction with the data warehouse architect on the development of logical data models.
• Used Erwin for data modeling.
• Created complex Stored Procedures , Triggers, Functions , Indexes, Tables, Views and other T-SQL code and SQL joins for applications.
• Implemented database standards and naming convention for the database objects. established data granularity standards, designed and built star and snowflake dimensional models
• Developed S SIS Packages to extract, transform and load (ETL) data into the data warehouse database from heterogeneous databases/data sources
• Designed Star Schema modeling creating Facts, Dimensions, Measures and Cubes in SSAS.
• Developed drill down and drill through reports from multi-dimensional objects like star schema and snow flake schema using SSRS and SharePoint server.
• Designed Aggregations and pre-calculating in SSAS .