Data Analytics
Amazon Web Services (AWS)
MongoDBCompany Profile:
Easebuzz is a payment solutions (fintech organisation) company which enables online merchants to accept, process and disburse payments through developer friendly APIs. We are focusing on building plug n play products including the payment infrastructure to solve complete business problems. Definitely a wonderful place where all the actions related to payments, lending, subscription, eKYC is happening at the same time.
We have been consistently profitable and are constantly developing new innovative products, as a result, we are able to grow 4x over the past year alone. We are well capitalised and have recently closed a fundraise of $4M in March, 2021 from prominent VC firms and angel investors. The company is based out of Pune and has a total strength of 180 employees. Easebuzz’s corporate culture is tied into the vision of building a workplace which breeds open communication and minimal bureaucracy. An equal opportunity employer, we welcome and encourage diversity in the workplace. One thing you can be sure of is that you will be surrounded by colleagues who are committed to helping each other grow.
Easebuzz Pvt. Ltd. has its presence in Pune, Bangalore, Gurugram.
Salary: As per company standards.
Designation: Data Engineering
Location: Pune
Experience with ETL, Data Modeling, and Data Architecture
Design, build and operationalize large scale 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 messaging systems such as Kafka/Kinesis for real time data ingestion and processing
Build data pipeline frameworks to automate high-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 greater scalability, etc.
Build the infrastructure required for optimal extraction, transformation, and loading of data from a wide variety of data sources using SQL and AWS ‘big data’ technologies.
Build analytics tools that utilize the data pipeline to 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 scientist team 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 enhance data pipeline architecture by designing and implementing data ingestion solutions.
Employment Type
Full-time
Subodh Popalwar
Software Engineer, Memorres
About EASEBUZZ
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Follow CutshortSubodh Popalwar
Software Engineer, Memorres