Monil Chothani
Data Engineer @Bank of America
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WORK HISTORY
Data Engineer @Bank of America
Designed,developed and implemented ETL processes using IICS data integration. Created autosys job to automatically trigger informatica jobs. Worked on Migration from SQL server to Oracle for target database. Created views to fetch data from various base table used for report purpose use by MicroStrategy tool. Created logical and phyical data models for audit purpose. Created data high level and low level data flow diagrams for the new server. Extensively used cloud transformations- Aggregator, Expression, Lookup, Filter, Router, Joiner transformations. Completed migration of workflow mapping from Informatica powercenter to IICS. Worked testing and migration of all parameter files for IICS. Developed Informatica cloud taskflow with multiple mapping task and taskflows. Involved in development, Unit testing and SIT phases of project. Analyzing new functional requirements and designing a solution for the same.
EDUCATION
Sinhgad Institute of Technology
Bachelor of Engineering (BEng), Computer Engineering
Shingad Institute of Technology
Bachelor of Engineering, Computational Science
Savitribai Phule Pune University
Bachelors, Computer Science
Shah And Anchor Kutchhi Engineering College
Master's Degree, Information Technology
SKILLS
ABOUT MONIL CHOTHANI
I’m a data engineer who enjoys solving real business problems through clean, reliable, and well-designed data pipelines. Over the past few years, I’ve worked across ETL development, data quality, metadata management, and workflow automation — mainly using Informatica (PowerCenter & IICS), SQL, Python, Oracle, Teradata, Autosys, and Collibra.Most of my work revolves around building end-to-end data workflows, improving performance, and making sure data is accurate and trusted. Whether it’s designing mappings in Informatica, optimizing a heavy SQL query, automating runs in Autosys, or validating data between source and target systems — I like understanding the “why” behind the requirement and then finding the cleanest way to implement it.I’m also quite passionate about data quality and governance. Tools like Collibra have helped me ensure that the data people rely on actually makes sense, has proper lineage, and follows governance rules. On the technical side, I frequently use Python for automation, API integrations, reconciliation checks, and small utilities that save execution time for the team.What motivates me most is seeing that the pipelines I build directly support reporting, analytics, and decision-making. I enjoy collaborating with teams, simplifying complex requirements, and improving processes step-by-step.I\'m always open to connecting with people working in data engineering, cloud integration, or anything related to transforming raw data into meaningful insights.
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