ERIC JOHN POZHOLIPARAMBIL

adgbdt@r.postjobfree.com *03 -554-7737

https://www.linkedin.com/in/ericpozholiparambil/

EDUCATION

Master’s in Information Systems Sept 2017-Aug 2019 Northeastern University Boston, MA, USA

Courses: Data management & Database design, Application Engineering and Development, Business Intelligence & Data Warehousing, Advanced Data Science, Business Analysis & Information Engineering, Big Data Systems & Intelligence, Big Data Architecture & Data Governance, Data Science Engineering Methods, Machine Learning and Python in Finance Bachelor of Engineering – Information Technology July 2013 - June 2017 University of Mumbai, India

Courses: Core and Advanced Database systems, Data mining, Data structures and Algorithms, Object oriented programming methodology, Operating systems, Computer Networks, Object oriented analysis and design, Web technologies, Artificial Intelligence, Cryptography and Cybersecurity TECHNICAL SKILLS

Programming Languages: SQL, Python, Java

Database: MySQL DB, SQL Server, PostgreSQL, Oracle DB, SQLite, Microsoft Access, Azure SQL DB Datawarehouse/ETL tools: Snowflake, Matillion, SQL Server Integration Services (SSIS), Talend, Alteryx, Big Query Analytical tools: Tableau, PowerBI, SSRS, SiSense, Looker, QlikSense, Excel Data design tools: SQLDBM, Toad Data Modeler, Toad Data Point Cloud tools: AWS Cloud 9 IDE, AWS S3, Google Cloud Storage (GCS), Google Cloud Platform (GCP) Other tools: Openfaas, Jira, Git/Bitbucket, SnowSQL, Microsoft Office suite, CodeSmith PROFESSIONAL EXPERIENCE

Data Engineer – Full Time at Decooda International Inc, Atlanta, GA, USA Oct 2019 –Present

• Built the infrastructure required for optimal Extraction, Transformation, and Loading of data from a wide variety of data sources across different data platforms like Snowflake and PostgreSQL in order to support all the application and business intelligence initiatives

• Used Matillion ETL to automate jobs that calculate financial metrics, resulting in a system that is 50 times faster than previously existing system

• Deployed a Lambda-like function on Openfaas using Cloud 9, that enables developers to transfer any desired file from S3 to Google Cloud Storage

• Led a team of Data Engineers in building a graph database called YetiDB, which consists of a great deal of information that leverages different types of Exploration such as Graph Searches, Event Prediction and Knowledge Mining

• Maintained entity relational diagrams, database schemas, views, stored procedures and supporting documentation

• Exploited rich data sets to create reports, stories and dashboards using Tableau and ran several POC’s in SiSense, Looker and KNIME Analytics Data Engineer Coop – Internship at Boston Private Bank and Trust Company, Boston, MA, USA Aug 2018 –Jan 2019

• Reviewed, developed, and designed financial data models, in conjunction with the application development team, created complex stored procedures, triggers, tables, cursors, views and SQL joins and made extensive use of dynamic SQL commands

• Managed database integration issues including migration between disparate databases using SQL Server Integration Services

• Created a script which automates creating DDL script, stored procedures, and functions which reduced manual effort by ~80%

• Developed Integration design to integrate the Salesforce data into SQL server

• Created quarterly reports and dashboards using Tableau by adopting various features such as drill down, hierarchy, bar/line chart, custom SQL ACADEMIC PROJECTS

Northeastern University, Boston, MA, USA Sept 2017 –Aug 2019 Data warehousing for a scalable retail business (SSIS, Talend, Tableau, PowerBI, Qlik Sense)

• Designed and developed a centralized data warehouse, pipelining retail data from diverse sources using Talend

• Implemented slowly changing dimensions, rejection codes, and performance tuning on a dataset with 48 million rows which sourced from multiple SORs (flat files, MySQL, SQL Server, Postgres and Oracle)

• Documented and governed the life cycle of data, including source-to-target mappings (Excel), transformations and data quality

• Built interactive dashboards to convey stories of retail sales and customer segmentation using Tableau, Qlik Sense and PowerBI Sentiment Analysis and Machine Learning on Yelp Review (Python, Machine Learning, NLP)

• Computed dataset of 5 million records & created a machine learning model where user ratings are generated based on real time input

• Applied natural language processing and feature extraction methods to predict reviews having null ratings

• Compared four different classifiers, of which logistic regression gave an accuracy of 90%