TECHNICAL SKILLS

Languages: Machine Learning, Decision Tree Classifier, Linear Regression algorithms, Python, SciPy, PySpark, Pandas, NumPy, MatLab, Automation Anywhere, UI Path, Pega, SQL, HIVE queries, Mainframes - COBOL, PLI and JCL.

Big Data Technologies/Tools: Hadoop, Hive, Impala, HBase, Sqoop, PIG, Spark and Splunk

Database: Netezza, MS-Access, Oracle, DB2 and IMS.

Tools: Data Scientist Workbench, Anaconda, Jupyter, PyCharm, IPython, IBM InfoSphere Information Analyzer, Trillium, Data flux, SAS/EG, HUE, UI Path, Automation Anywhere, Pega, Data Studio, SQL developer, MS Office - Word, Excel, PowerPoint, Visio, RMS and SVN

PROFESSIONAL EXPERIENCE

Confidential, Detroit, MI

Data Analytics Lead

Responsibilities:

• Data Analysis is carried out using HIVE, Impala, HBase, Sqoop and PIG tools in Cloudera Distribution Hadoop ecosystem.
• Sqoop importer to extract data from Oracle RDBMS tables into HDFS flat files/Hive tables during non-business hours through HUE.
• Data from EDW/RDBMS is moved as flat files to Cloudera Distributed Hadoop (CDH) environment and Hive/Impala tables are created.
• PIG Script to apply transformations to fix data type compatibility, removed unwanted columns and store back the resultant file in HDFS.
• SQOOP to add daily delta updates into existing HIVE directory
• OOZIE job to schedule Python, PIG and HIVE script in sequence
• Data elements required are identified and joined using HIVE HQL queries to create required view.
• Exploratory Data Analysis, Profiling and Assessment to evaluate data for accuracy and quality using Python libraries MATLAB, NUMPY and PANDAS.
• Python scripts to automate business rules to find co-relation among different data elements
• Analyze completeness and cleanse anomalies using advanced Data Science imputing techniques through PANDAS.
• Identifying correlation among features, perform advanced feature engineering technique.
• Developed basic predictive MODELs using Classification and Regression algorithms using scikit-learn python library.

Confidential

Data Architect

Responsibilities:

• Management and implementation of database models, data flow diagrams, structures and data standards to support robust data management infrastructure.
• Designed ETL strategy for large-scale data conversion, design and implementation across different platform including Legacy to ERP.
• Develop Enterprise Data Strategy road map for Confidential initiative, identifying business drivers, reporting metrics and establish data governance model.
• Build DQ framework for CIA, in-house or boxed solution for end-to-end DQ cycle and BPM.
• Develop best practices for data management, maintenance, reporting and security.
• Assist team in data management projects when needed.
• Integrate and automate DQ toolsets and functions within DQ framework.

Confidential

Data Architect

Responsibilities:

• Identified Use Cases with Business Teams for Robotics PoC.
• Actively participated and collaborated with architecture team on down selecting three Confidential Tools/Vendors from 20+ tools.
• Identified two uses cases for Proof of Concept one each from AML and Finance.
• Configured Confidential tools UiPath, Pega (Open Span) and Automation Anywhere (AA) in Ally Test Lab.
• Completed Use Case development and conducted demo of working prototype to AML and Finance business leaders.
• Demonstrated Confidential /AI prototypes and its benefits to Corp tech and CIA leadership.
• Rated Confidential tools used in POC as per Ally Architectural and Functional requirements.
• Collaborating with Corporate Technology team to procure Automation Anywhere tool for Confidential project execution this year.

Confidential

Data Architect

Responsibilities:

• Designed and Developed data model, process model to accommodate Confidential requirements in Confidential Data Lake initiative.
• Developed file specification and reference data specifications to capture customer consent data by LOB’s.
• Reviewed each LOB’s process, system and data requirements to capture and communicate revocation details to enterprise system.
• Designed and Developed integration process in Confidential system to create/update Customer Master Data using details from all LOB’s and manage duplication.
• Designed system, interface, incoming and outgoing data from LOB’s and CIA system to provide sign off.

Confidential

Senior Data Analyst

Responsibilities:

• Identified impacts of IA 11.5 Confidential within DQ.
• Developed comprehensive deployment instructions for IA 11.5 Confidential .
• Tested entire DQ cycle in 11.5 to identify gaps, compatibility issues and defects.
• Seamlessly implemented changes into production.
• Coached and mentored GDC resources to leverage 11.5 features such as SQL Virtual tables to write complex SQL rules.

Confidential, Bloomington, IL

Senior Data Analyst

Responsibilities:

• SQOOP to extract data from DB2 Mainframe into HDFS flat files / Hive tables during non-business hours.
• Data from mainframe is moved as flat files to Hadoop environment and Hive tables are created.
• Nine-node cluster is currently maintained using Horton work distribution.
• Removed unwanted columns using PIG Script and store back the resultant file in HDFS.
• Created External table on top of the directory where PIG resultant file is stored.
• HIVE HQL script is written to compare two tables and store the result into table, which is exposed to external world (Pivot table, TABLEAU).
• SQOOP to add daily delta updates into existing HIVE directory.
• Helped scheduling team set up a OOZIE job to execute PIG and HIVE script in sequence.
• Responsible for building scalable distributed data solutions using Hadoop.
• Writing scripts to automate the offloading of files one environment into Hadoop environment.
• Solving error by looking at corresponding log files.
• Worked with analyst and test team for writing Hive Queries.

Confidential

Senior Data Analyst

Responsibilities:

• DQ framework comprehends assesses, analyze, report and solve data quality problems with proactive management.
• Configured different data sources against Trillium and resolved many issues.
• Profiled, assessed and developed DQ rules on Trillium / SQL and implemented in production.
• Automated monthly DQ report validation using SQL’s.
• Proposed and created Materialized view to enhance SQL performance of DQ rules and DQ report metric calculations.
• Mentored intern on DQ activities, proposed process documentation, artifacts for deliverables.
• Identified DQ metric calculation for new engagement lining with existing standards.

Confidential

Data Analyst

Responsibilities:

• Designed Target IDAA DB2 Tables for hierarchical IMS DB.
• Built data models, data Mapping document and Confidential rules.
• Developed COBOL, PLI programs to extract IMS data to load.
• Document corporate metadata definitions for enterprise data stores, established naming standards, data types, volumetric and domain definitions.
• Developed DQ rules to analyze data, profiling stats and identify anomalies.
• Developed programs to calculate DQ metrics for DQ reporting in Cogno’s dash board.

Confidential, Chennai, TN

Data Analyst

Responsibilities:

• Project planning for all new Data Quality engagements.
• Extracting data from hierarchical Mainframe IMS databases and loading into Trillium for Confidential .
• Develop matching COBOL copybooks using metadata information to create entities.
• Data profiling, Assessing and creating reports.
• Brainstorming with Business and SME’s to develop and configure business rules.
• Execute rules and Identify anomalies.
• Perform Cost / Benefit analysis on fixing anomalies with Business, SME’s and Sponsors.
• Summarize and present assessment findings to Business partners, Data Business analyst, subject matter experts and stakeholders.
• Writing requirement specification for DATA cleansing activities.

Confidential

Mainframe Application Developer

Responsibilities:

• Coordinate and Communicate with Onsite lead on engagements.
• Coordinated DBVal application for big integrated projects by identifying impacts and implementing changes.
• Develop / Modify COBOL/PLI programs as per new enhancement requirements.
• Create component specs, develop programs, test and prepare UTR, and making SCIT entries (document changes) and upload into RMS (Revision Management System).
• Support and sustain DBVal programs, Job monitoring and Daily/Monthly Control - D reports.
• Writing and executing SQL’s to fix discrepancies in Database that are identified through Database validation.