• US Citizen

• Green Card

• EAD (OPT/CPT/GC/H4)

• H1B Work Permit

• Corp-Corp

• W2-Permanent

• W2-Contract

• Contract to Hire

• Consulting/Contract

• UG :- - Not Required

• PG :- - Not Required

• No of position :- ( 1 )

• Post :- 5th Mar 2025

Following is a summary of the essential functions for this job.  Other duties may be performed, both major and minor, which are not mentioned below.  Specific activities may change from time to time. 

Builds, manages, and implements the data pipeline capabilities including data modeling, process design and overall data pipeline architecture, dashboard/report development and all phases of the ETL (extract, transform, and load) processes.

Analyzes information to determine business needs from intake requests.  Implements effective technical solutions by providing problem analysis and resolution in a timely manner as well as explains and interprets complex, difficult, or sensitive information.

Takes a new perspective on existing solutions to solve problems of moderate to high complexity and exercise judgment based on the analysis (e.g. modeling, testing, etc.) of multiple sources of information.

Develops technical solutions by providing problem analysis and resolution in a timely manner and explain and interpret complex, difficult, or sensitive information.

Lead small data engineering projects with manageable risks and resource requirements; plays significant roles in larger, more complex initiatives.

Hands-on knowledge on Python code to build custom scripts task optimization.

Design, develop, and maintain complex ETL workflows using SSIS for data integration tasks.

Create efficient and scalable data pipelines to move data between multiple sources and destinations.

Work with large datasets to ensure proper data transformations, cleansing, and aggregation.

Troubleshoot, debug, and optimize SSIS packages and SQL queries for better performance.

Design and implement automated solutions to monitor, test, and validate ETL workflows.

Integrate and load data from various sources like relational databases, flat files, APIs, etc.