Aravind Kumar Anugula

• Formulated and established robust analytics for shipment tracking and carrier data quality analysis.
• Built a Data Platform Tool to ingest data from various sources.
• Lead the transition from batch analytics to real-time analytics, enhancing data processing speed and accuracy.
• Designed and implemented scalable data pipelines using Apache Kafka and Apache Spark Structured Streaming for real-time data processing.
• Migrated Shipment Tracking Analytics from distributed models to unified models.
• Optimized Snowflake ELT pipelines, achieving a 50% reduction in data processing costs.
• Migrated legacy Snowflake SQLs into DBT tool.
• Added data quality checks to ensure data reliability.

Project44's Data Analytics Platform enables customers to view real-time and historical shipment performance, select the optimal logistics provider, and allows carriers to monitor shipment health metrics and track process improvements.

• Leading multiple teams in Data Platform
• Built Data Ingestion Platform, self service tool to ingest data from various sources
• Implemented best practices and standards across the Data team
• Coordinate across retail supply chain, sales, inventory functional teams of data scientists, analysts, product managers, engineers and setup data pipelines for their business operations.
• Designed and developed RDBMS, Streaming , File ingestion connectors
• Built data transformation accelerators
• Designed robust architecture to support HA, Scalability and Data Quality.
• Collaborate with other teams to incorporate their use cases.
• Collaborate on ETL (Extract, Transform, Load) tasks, maintaining data integrity and verifying pipeline stability
• Integrated Great Expectation tool to ensure pipelines Data Quality
• Coaching and mentoring engineers on best-in-class data engineering technologies

Data Ingestion Platform tool is self service tool used by lowe's organization to ingest data from various external sources into the Hadoop and transform as per business usecases.

Users can launch data pipelines in few minutes without knowledge on bigdata skills.

• Migrated existing legacy data pipeline stack from ELK to Hadoop stack
• Designed real time streaming data pipeline to detect treats and notify users.
• Designing and architecting large scale distributed data management and analytics applications
• Closely worked with devops team to build Scalable , Highly Available and Robust infra setup on AWS cloud platform.
• Created data pipeline to process and store massive amount of data in data lake.
• Developed test automation framework using Robotframework for complete data pipeline quality.
• Perform proof-of-concept (POC) on new technologies and approaches.

• Designed Modules: Data Batch Processing, Data Analytics, Code development, Unit Testing, bug fixes
• Lead Team members in development activities and work individually on product backlog.
• Collaborates with product owner and stakeholders in order to understand business needs and provide technical solutions.
• Make sure the right modelling is being done, to know that qualities like performance are going to be met.
• Guide in preparation of technical design documents. Ensure that documentation is in place and maintained
• Provide guidance to the dev team on the best possible implementation/planning during execution of a task.