Data Engineer

About the Company

Easebuzz is a payment solutions (fintech) company that enables online merchants to accept, process, and disburse payments through developer-friendly APIs. We are focused on building plug-and-play products—including payment infrastructure—to solve end-to-end business challenges across sectors.

We’re at the center of all things fintech: payments, lending, subscriptions, eKYC—you name it. Easebuzz is where innovation meets execution.

We have been consistently profitable and continue to scale rapidly, having grown 4x in the past year alone. Backed by a strong product roadmap and execution, we recently closed a fresh funding round of $30 million in 2025, led by leading VC firms and strategic investors. This comes in addition to our earlier $4 million fundraise in March 2021.

Easebuzz has been granted Full Authorization from the Reserve Bank of India (RBI) for payment aggregator license in 2025.

Our corporate culture is built on openness, ownership, and collaboration. We are an equal opportunity employer and celebrate diversity across all levels. At Easebuzz, you’ll find yourself working with passionate colleagues who are committed to growing together.

Headquartered in Pune, we also have a presence in Delhi, Mumbai, Kolkata, Bengaluru, and Gurugram.

Headquartered in Pune, we also have a presence in Delhi, Mumbai, Kolkata, Bengaluru, and Gurugram.

Experience with ETL, Data Modeling, and Data Architecture

Design, build and operationalize largescale enterprise data solutions and applications using one or more of AWS data and analytics services in combination with 3rd parties

- Spark,EMR, DynamoDB, RedShift,Kinesis, Lambda, Glue.

Experience with AWS cloud data lake for development of real-time or near real-time use cases

Experience with messagingsystems such as Kafka/Kinesis for real time data ingestion and processing

Build data pipelineframeworks to automatehigh-volume and real-time data delivery Create prototypes and proof-of-concepts for iterative development.

Experience with NoSQL databases, such as DynamoDB,MongoDB etc Create and maintain optimal data pipeline architecture,

Identify, design, and implement internal process improvements: automating manual processes, optimizing data delivery, re-designing infrastructure for greaterscalability, etc.

Build the infrastructure required for optimalextraction, transformation, and loading of data from a wide variety of data sources using SQL and AWS ‘big data’ technologies.

Build analytics tools that utilizethe data pipelineto provide actionable insights into customer acquisition, operational efficiency and other key business performance metrics.

Work with stakeholders including the Executive, Product, Data and Design teams to assist with data-related technical issues and support their data infrastructure needs.

Keep our data separated and secure across national boundaries through multiple data centers and AWS regions.

Create data tools for analytics and data scientistteam members that assist them in building and optimizing our product into an innovative industry leader.

Evangelize a very high standard of quality, reliability and performance for data models and algorithms that can be streamlined into the engineering and sciences workflow

Build and enhancedata pipeline architecture by designing and implementing data ingestion solutions.

Akill Sets required - SQL, Pyspark and Understanding of Distributed computing are must, AWS EMR, stream processing, kafka, Pinot and Flink are appreciated

Employment Type

Full-time