Detail-oriented Leader with 8+ years of experience designing, development and maintaining highly scalable, secure and reliable data platform as well as managing medium sized team globally. Accustomed to working closely w…
Detail-oriented Leader with 8+ years of experience designing, development and maintaining highly scalable, secure and reliable data platform as well as managing medium sized team globally. Accustomed to working closely with system architects, data architects and design analysts to understand business requirements to develop comprehensive data models. Proficient at developing database architectural strategies at the modeling, design and implementation stages.
Detail-oriented Leader with 8+ years of experience designing, development and maintaining highly scalable, secure and reliable data platform as well as managing medium sized team globally. Accustomed to working closely with system architects, data architects and design analysts to understand business requirements to develop comprehensive data models. Proficient at developing database architectural strategies at the modeling, design and implementation stages.
Leads the Cloud Data Platform for Investment Management business, with a size of 10-12 members globally.
Promoted twice in the span of 3 years of joining the firm.
Member of the firm's Core Architecture Group and Databricks Core Developer Group.
Designed and developed Data Warehousing and Data Lake solution for Investment Management Business on Cloud using Snowflake.
Architected solution for Data Pipeline called as GLIDE (Glue for Ingestion and Data Exchange) a Platform to easily configure meta-data driven data pipeline both Cloud and on-prem using Databricks, Snowflake and Airflow.
Designed a solution of integrating Data Quality framework using Great Expectation Library to be run as part of the Data Ingestion.
Designed a comprehensive access control / masking solution for the MS Investment Management Business (Post Eaton Vance Acquisition) using native Snowflake features and integrated with LDAP.
Developed automated ETL code generation process for incremental Data Warehouse use cases along with a robust DevOps process which is integrated with the code generation used for DB2 and Snowflake.
Created re-useable PySpark artefacts on Databricks for configuration driven use cases like Azure Data Lake Storage / Amazon S3 to Snowflake or Delta Lake data loading along with transformations and pre-processing like XML/JSON Flattening, Reference Data Enrichment.
Designed and Developed a configuration driven Streaming data framework based on Databricks Delta Live Tables.
Worked as a Consultant for Morgan Stanley Investment Management Technology division for 2 years before joining the client firm.
Started as a Junior Developer handling project requirement for regulatory reporting and analytics.
Won multiple awards for Innovation and Leading with Exceptional Ideas from the client side.
Worked on creating multiple Data Warehouse pipeline for low latency use cases.
Developed multiple automation suites like Generic RFB, which is a configuration driven python utility to check the data accuracy between two systems using Pandas Library, which also includes checks like Data Quality and Referential Integrity.
Designed and Developed DW Autobot which is a JSON Config based data pipeline automation tool that is used for enhancing existing feed mappings updating DB2/Snowflake Database DDL, Stored Procedures, Informatica Mappings and deployed through Liquibase using CI/CD process.
Developed automated ETL code generation process for incremental Data Warehouse use cases along with a robust DevOps process which is integrated with the code generation used for DB2 and Snowflake.
Created re-useable PySpark artefacts on Databricks for configuration driven use cases like Azure Data Lake Storage / Amazon S3 to Snowflake or Delta Lake data loading along with transformations and pre-processing like XML/JSON Flattening, Reference Data Enrichment.
Designed and Developed a configuration driven Streaming data framework based on Databricks Delta Live Tables.
In this role I worked as a Consultant for Morgan Stanley Investment Management Technology division for 2 years before joining the client firm.
Started as a Junior Developer handling project requirement for regulatory reporting and analytics.
Won multiple awards for Innovation and Leading with Exceptional Ideas from the client side.
Worked on creating multiple Data Warehouse pipeline for low latency use cases.
Developed multiple automation suites like Generic RFB, which is a configuration driven python utility to check the data accuracy between two systems using Pandas Library, which also includes checks like Data Quality and Referential Integrity.
Designed and Developed DW Autobot which is a JSON Config based data pipeline automation tool that is used for enhancing existing feed mappings updating DB2/Snowflake Database DDL, Stored Procedures, Informatica Mappings and deployed through Liquibase using CI/CD process.
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