Key Responsibilities: Data Engineering & Architecture - Design, build, and operationalize enterprise-scale data solutions using AWS services (Spark, EMR, DynamoDB, RedShift, Kinesis, Lambda, Glue).

- Build data pipeline frameworks for high-volume, real-time data ingestion and processing.
- Develop and maintain optimal ETL architecture and workflows.
- Work with NoSQL databases (DynamoDB, MongoDB) and messaging systems (Kafka, Kinesis).
- Implement internal process improvements to automate manual processes, optimize data delivery, and redesign infrastructure for scalability. Analytics & Insights - Build analytics tools to provide actionable insights into customer acquisition, operational efficiency, and key business metrics.
- Support data scientists and analytics teams with data infrastructure and tools.




- Evangelize high standards of quality, reliability, and performance for data models and algorithms. Cloud & Data Security - Utilize AWS cloud data lake solutions for real-time or near real-time use cases.
- Ensure data security across multiple regions and compliance with data separation standards. Collaboration & Stakeholder Support - Work with Executive, Product, Data, and Design teams to resolve data-related technical issues.
- Assist teams in leveraging data infrastructure to optimize product performance.
- Create prototypes and proof-of-concepts to support iterative development.

📌 Associate Manager (Research) (Pune)
🏢 Easebuzz
📍 Pune