Binit Chowdhary

Client : LSEG

Project :

Working on developing platform and solution for fintech domain to create data products for end clients. This is in collaboration with Microsoft.

Key Deliverables :

• Designed and developed automated tool for LDM to PDM conversion for the data to be served to the client.
• Worked with downstream team to serve the LDM PDM data to integrate it with Purview for establishing governance around this.
• Identified performance issues, came up with ideas and implemented solution to mitigate the issues.
• Worked on implementing XML parsing framework.

Skills : Microsoft Fabric, SQL, PySpark, Python, Azure Data Factory(ADF), Azure Data lake(ADLS), Data Warehousing, Azure Synapse, ETL, Azure DevOps, GitHub, Storage Accounts etc.

Client : Internal

Project :

Working on developing and maintaining pipelines to support Capital markets/Valuations business of JLL globally. End goal is to make property data available for Smart Property Application. This highly scalable application is used by business to drive insightful/data backed investments by investors. This helps investors realize their investment needs/returns more effectively.
To achieve this, I am responsible to make data available in the required format which could be loaded to Application.
This starts with ingesting data from various sources like SFTP,RDBMS,API etc. followed by transforming data to JLL common model for silver layer consumption. Next step is to transform data to a scalable data model and store in Data Hubs followed by generating the final data file which would be consumed by end application.

Key Deliverables :

• Implemented Data Hub for Global Data Sources as existing was region specific Data Hubs for storing Facts and Dimensions.
• Took initiative and migrated Data Hub from Azure SQL server to Data Lake Delta.
• Tuned performance of existing Stored procedure and brought down run time by approx. 4-5 times.
• Tuned performance of Data bricks scripts and brought down load/run time from ~11 hrs to less than 2 hrs.
• Developed incremental process to identify incremental records and merge to data hub. Helped in load time improvement from ~5 hrs to 25-30 mins.
• Worked with automated test cases and ensured code coverage is per industry standards.

Skills : SQL, PySpark, Python, Databricks, Azure Data Factory(ADF), Azure Data lake(ADLS), Data Warehousing, Azure Synapse, ETL, Azure SQL Server, Azure Functions, Azure DevOps, GitHub, Storage Accounts etc.

Client : JLL( Deployed as Senior Data Engineer @JLL on Contract)

Project : Deployed to JLL as contractor hence, added details under JLL.

Key Deliverables : Deployed to JLL as contractor hence, added details under JLL.

Skills : SQL, PySpark, Python, Databricks, Azure Data Factory( ADF), Azure Datalake(ADLS), Azure Synapse, Data Warehousing, ETL, Azure Sql Server, Azure Functions, Azure DevOps, GitHub, Storage Accounts etc.

Client : Cerner

Project :

Worked on developing and maintaining data pipelines to support Finance and Supply Chain dataset. This was modernizing project to migrate reporting data from on-premise legacy to cloud.

To achieve this, was responsible to ingest data from ERP system OLTP database to Data lake. Followed by combining initial with incremental data to produce daily snapshots using Data bricks. Data transformation was done on snapshots to produce required dimensions and facts using Databricks. This was loaded to Snowflake to support the BI/reporting needs. Was done by understanding transformations in legacy ETL, followed by creating logic in new platform leveraging Databricks.

Key Deliverables:

• Implemented logic to load incremental data instead of full load based on business requirement.
• Developed utility notebook with functions to perform merge for SCD 1 and 2 in Snowflake.
• Developed ADF pipeline to read and load data from Oracle OLTP to data lake.
• Developed orchestration pipeline using ADF to enable Databricks notebooks to run per schedule.
• Developed merge script in Databricks to merge initial and incremental data to produce daily snapshots.

Skills : SQL, PySpark, Python, Databricks, Azure Data Factory(ADF), Azure Datalake( ADLS), Azure Synapse, Data Warehousing, ETL, Snowflake, Kafka, Azure DevOps, GitHub, Key Vaults, Storage Accounts etc.

Client : North America Truck Manufacturer

Project :

Led team of 10 developers to support the Finance and Supply chain development effort. Was responsible for Requirement analysis, solutioning, technical design and development in FSCM.

Key Deliverables:

• Worked on developing integration of data from on-premise to cloud for analytics.
• Moved Finance data to ADLS followed by developing logic to create and load the dimensions and facts.
• Performed data crunching to figure out Past Due invoices for which Org did not charge penalty and informed Business. This was appreciated by client end Director.
• Designed and developed interface to fetch real time financial reports from 3rd party repository and show in user interface.
• Developed Interface to receive Time data from Kronos to load into PeopleSoft Time.

Skills : Azure Data Factory, Azure Databricks, Pyspark, Azure Sql Server, SQL, Peoplecode, RDBMS, AE, BI Publisher, IB etc.