NEERAJ KUMAR

Project : DSS Dataiku Platform Enablement and Optimization

• Collaborated with the ETL operations team to develop strategies and conceptualize best practices for the DSS Dataiku platform.
• Reengineered existing ETL workflows to improve performance by identifying bottlenecks and optimizing code accordingly.
• Led a team of six Data Engineers, providing mentorship and guidance.
• Successfully implemented DSS ETL best practices across 150+ projects.
• Optimized DSS recipes, including SQL, Python, and visual recipes (e.g., Prepare, Sync).
• Assisted multiple teams in creating, archiving, optimizing, and setting up Dataiku projects, ensuring efficient workflow management and project execution.
• Received client recognition for optimizing multiple ETL projects and deploying them on the Auto node platform.

Project : SDOH (Social Determinants of Health)

• Build a centralized SDoH Data Lake, enabling enterprise-wide access and supporting data-driven decision making for key business stakeholders.
• Collaborated cross-functionally with RWE & Commercial colleagues to prioritize and identify public SDoH Data Sources to include in the RWD Data Mart
• Conducted data profiling and data modeling of 25 publicly available SDoH datasets, subsequently categorizing them into 18 SDoH categories using a developed data lake.
• Utilized Python web scraping techniques to extract data from publicly available websites, streamlining data collection and enhancing data accessibility for analysis.
• Led a team of three Data Engineers, providing mentorship and guidance.
  

Project: CTDI(Competitive Trial Design Intelligence)

• Worked with business to gather, standardize, harmonize & visualize clinical trials information from unstructured data sources to aid trial designs.
• Developed and implemented a data ingestion and processing pipeline for unstructured data using Python, with outputs published to Elasticsearch (No SQL) for web application integration
• Configured AWS services including EC2, IAM, API Gateway, Lambda, and RDS to establish a data pipeline. Developed over 30 APIs in Python utilizing AWS Lambda and API Gateway, while leading and mentoring a team of 4 data engineers
• Collaborated cross-functionally with front-end, data science and data engineering teams
  

Project : APTP (Accenture Post Trade Processing)

• APTP is utilized to enhance post-trade processing, specifically in the areas of Trade Confirmation, Clearing, Settlement, Reconciliation, and Risk Management.
• Developed a data warehouse integrating data from external vendors and corporate sources, including Oracle 10g, flat files, Microsoft Excel files, and XML files.
• Worked with business users/Analytics team, data architects to identify the business requirements and developed designed document for ETL flow.
• Tuned performance related issues faced on Production.
• Migrated on-prem database ( MS SQL) to AWS based database RDS using AWS DMS and SCT service