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.

Skills: Data Modeling, Etl, Data Architecture, data engineering , Aws, Data Pipeline

Experience: 0.00-4.00 Years

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