Contributing to core data and AI platform engineering with a focus on Java application development, scalable pipelines, data quality systems, and agentic AI architecture. Drive end-to-end feature design, platform modernization, and engineering mentorship.

Key Contributions:

1. Enhanced data quality and anomaly detection systems by upgrading rules engines, adding scoring capabilities, enabling secure migrations, and automating monitoring through Prometheus/Grafana.

2. Led development of a GenAI-powered pipeline builder that enables users to create and manage pipelines using natural-language commands, significantly reducing manual effort.

3. Improved pipeline orchestration and scheduling, including support for multi-instance execution and more reliable queue management.

4. Designed agentic AI and GPT-based enhancements using the MCP framework, standardizing how AI features are delivered across the platform.

5. Mentored an engineering intern and built a dockerized multi-version testing environment to simplify local development and reduce setup time. Designed and generated feature specific synthetic data for testing and validation on local environment

6. Contributed to API development, release management, and code quality improvements through consistent code reviews and team support.

1. Working on data pipelines for processing data from various sources that give more insights to help predict probable customers helping the process of targeted marketing.

2. Working with website crawling, large scale distributed system design and data processing;

Big data technologies used : Hadoop, Spark, Hive

Languages : Java, Python, Jinja template

Data Analysis tools used : Jupyter Notebook, Zeppelin Notebook

AWS Stack used : EMR, S3, Dynamo DB, EC2

Dun & Bradstreet acquired Lattice Engines in July 2019.

Lattice delivers data-driven business applications that help companies of all sizes market and sell more intelligently. My job duties are as follows :

 Working with website crawling, large scale distributed system design and data processing;

 Using expertise in Python, Java, T-SQL, AWS, architecture/design principles/object design and strong

analytical, problem solving skills;

 Working with HTTP and webservers, DOM parsing and other text mining/retrieval;

 Utilizing information retrieval concepts, machine learning and natural language processing; and

 Working with short release cycles, Agile/Scrum and TDD

1.Develop standardized approaches to deliver customer level insights from raw data

2. Establish and maintain big data processing platform

3. Build Hadoop-based data management applications

4. Design Hive/HBase distributed data warehouse

5. Design, develop, maintain cross-platform ETL processes and MapReduce/Hive data processing workflows

6. Build Hive/HBase data marts

7. Maintain dimensions and reference lookup dictionaries

8. Support client services teams

9. Manage, customize, and execute cloud-based data processing supporting multiple clients

10. Administration of relational databases, capacity plans, infrastructure and storage design

11. Oversee and execute data migration from existing data stores

11. Application/implementation of custom analytics

13. Develop standards, guidelines, and QA processes to ensure highest data quality and integrity

14. Work with modeling analysts to improve customer segmentation, variable selection and behavioral modeling methodologies

15. Commit to writing production quality code that integrates into their Big Data Platform (Hadoop)

16. Work in a cross-functional team of data engineers, data scientists and product managers

17. Lead an independent research effort to discover new products