Aditya Laddha

Standardized and built end-to-end integrations using SnapLogic across SAP, GCP, Salesforce, Ariba, RPA, and SFTP. Integrated with DataDog and Chronosphere for observability and led cutover planning and deployments.

Analyzed business requirements and translated them into technical designs. Refactored Time-Card and UPC integrations, and architected a custom administrative utility pipeline for user account auditing.

Designed and implemented end-to-end data pipelines using Apache NiFi, Kafka, MongoDB, MySQL, and Python. Built pre-processor and post-processor flows for metadata auditing and threshold-based control.

Engineered and performance-tuned multi-system data pipelines across Workday, Snowflake, Active Directory, Oracle, AWS S3, and more. Coordinated with third-party vendors and managed production deployments.

Provisioned Snowflake schemas and optimized bulk data ingestion from AWS S3. Authored SnapLogic design documents, established version control with GitHub, and led training and technical interviews.

Led L3 production support and pipeline administration for 50+ interfaces and 100+ integrations. Engineered automated utility pipelines and collaborated with SnapLogic vendor support for platform-level resolutions.

Built scalable ingestion pipelines for a pharmaceutical client, extracting data from Oracle, Veeva, and flat files into a Data Lake and AWS S3 into Amazon Redshift. Created source-to-target mapping documents and implemented SCD-1 logic.

Grade: 7.81

Bachelor of Engineering in Computer Science and Engineering from Prof. Ram Meghe Institute of Technology & Research, Badnera, affiliated with Sant Gadge Baba Amravati University, graduating in 2015.