• 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 :- 17th Dec 2025

The person on this role will play a crucial role in building scalable and cost-effective data pipelines,  data lakes, and analytics systems.

• Data Ingestion: Implement data ingestion processes to collect data from various sources, including databases, streaming data, and external APIs.

• Data Transformation: Develop ETL (Extract, Transform, Load) processes to transform and cleanse raw data into a structured and usable format for analysis.

• Data Storage: Manage and optimize data storage solutions, including Amazon S3, Redshift, and other AWS storage services.

• Data Processing: Utilize AWS services like AWS Glue, Amazon EMR, and AWS Lambda to process and analyze large datasets.

• Data Monitoring and Optimization: Continuously monitor and optimize data pipelines and infrastructure for performance, cost-efficiency, and scalability.

• Integration: Collaborate with data scientists, analysts, and other stakeholders to integrate AWS-based solutions into data analytics and reporting platforms.

• Documentation: Maintain thorough documentation of data engineering processes, data flows, and system configurations.

• Scalability: Design AWS-based solutions that can scale to accommodate growing data volumes and changing business requirements.

• Cost Management: Implement cost-effective solutions by optimizing resource usage and recommending cost-saving measures.

• Troubleshooting: Diagnose and resolve AWS-related issues to minimize downtime and disruptions.

• Qualifications

Must Have:

• Strong experience with AWS services on big data platforms.

• Strong Python experience in building Dash application in AWS

• Spark

• Shell scripting and Linux knowledge

Nice to have:

• Investment Knowledge preferred

• Looking for candidates who have worked in Investment/Finance space

• Machine Learning Skills

Qualifications:

• Educational Background: A bachelor's degree in computer science, information technology, or a related field is typically required.

• A master's degree is preferred with GPA of 3.8+Problem-Solving:

• Strong analytical and problem-solving skills to address complex data engineering challenges.

• Communication Skills:

• Effective communication and collaboration skills to work with cross-functional teams