As a Tech Lead in Data Engineering at Harman International, I specialize in graph databases, particularly Neo4j, with extensive experience in designing robust graph DB models, data structuring, and setting up distributed clusters. My expertise lies in building scalable data architectures that support complex business logic, ensuring high performance and efficient data retrieval.In my role, I oversee the implementation and monitoring of graph database solutions, utilizing my proficiency in technologies such as Apache Kafka, Python, Neo4j, Pyspark and PostgreSQL. I collaborate closely with cross-functional teams to design and optimize data architectures that drive data engineering operations, ensuring our systems meet business needs and scale effectively.With a passion for solving intricate data problems, I’m committed to delivering cutting-edge solutions that enhance data-driven decision-making.

• Designed, implemented, and maintained multi-node data clusters for efficient data retrieval and storage utilizing Python, PySpark,PostgreSQL, Neo4j, Elasticsearch, Kafka, Airflow, GCP Dataproc and Databricks 'All-purpose' clusters.• Developed and optimized data processing pipelines for large-scale analysis and transformation, improving data insights and decisionmaking.• Collaborated with cross-functional teams to integrate Neo4j, Elasticsearch, and Kafka solutions into existing systems.• Created and managed scalable and fault-tolerant ETL pipelines, ensuring reliable data processing workflows. Led initiatives for datamodeling, indexing strategies, and query optimization to enhance performance and efficiency.• Applied problem-solving skills and agile methodologies to tackle technical challenges and enhance data engineering processes. Facilitatedcommunication and collaboration within onsite and offshore teams to ensure project alignment and timely delivery.

• Responsible for data scraping, data cleansing, data-models designing, and data storage.• Involved in multiple POC’s & migrations as a key resource (solutions built using Python, Neo4j, SQL, Kafka).• Working collaboratively with the Onsite and offshore clients and team.Client: Raymond James

Spearheaded implementation of platform-level microservices, enhancing scalability and efficiency of GEP Solutions' systems.Translated intricate business requirements into comprehensive technical specifications, ensuring alignment between client needs and product functionalities.Played a pivotal role in multiple Proof of Concepts (POCs) and migrations, leveraging a diverse tech stack including Neo4j, ELK, Kafka, Pyspark, Airflow, Python, and C#.Architectured enterprise search architecture and technical solutions, driving seamless application deployment through Azure CI/CD processes.Fostered collaborative teamwork between onsite and offshore teams, facilitating effective communication and coordination of scrum events.Led the development of GEP DAC Layer, a critical microservice validating user access for requested data, utilizing Python, Pandas, Neo4j, Elastic Search, SQL, Handlebars, C# .NET Core, Azure Table Storage, and Kafka.Orchestrated the creation of GEP State Machine, enabling dynamic document management based on user access and document status, employing Python, Pandas, Neo4j, Elastic Search, SQL, Handlebars, C# .NET Core, Azure Table Storage, and Kafka.Served prestigious clients including Chevron, Pertamina, Petronas, Bank of America (BOFA), CITI Bank, Tata Steel, Danone-Food, and Roche-Pharma, ensuring delivery of tailored solutions meeting their unique needs and objectives.

Implemented production environment cloud infrastructure for NoSql Search Database (Elasticsearch) | Implemented dashboards for analysed search data