Data Engineer

About PayU
PayU, a leading payment and Fintech company in 50+ high-growth markets throughout Asia, Central and Eastern Europe, Latin America, the Middle East and Africa, part of Prosus group, one of the largest technology investors in the world is redefining the way people buy and sell online for our 300.000+ merchants and millions of consumers. 
As a leading online payment service provider, we deploy more than 400 payment methods and PCI-certified platforms to process approximately 6 million payments every single day. 
Thinking of becoming a PayUneer and you are curious to know more about us? Read more about the life in PayU here 
Role: Data Engineer
Company: PayU
Location: Gurgaon /Bangalore/ Mumbai
About Company:
PayU is the payments and fintech business of Prosus, a global consumer internet group and one of the largest technology investors in the world. Operating and investing globally in markets with long-term growth potential, Prosus builds leading consumer internet companies that empower people and enrich communities. The leading online payment service provider in 36 countries, PayU is dedicated to creating a fast, simple and efficient payment process for merchants and buyers.
Focused on empowering people through financial services and creating a world without financial borders where everyone can prosper, PayU is one of the biggest investors in the fintech space globally, with investments totalling $700 million- to date. PayU also specializes in credit products and services for emerging markets across the globe. We are dedicated to removing risks to merchants, allowing consumers to use credit in ways that suit them and enabling a greater number of global citizens to access credit services. Our local operations in Asia, Central and Eastern Europe, Latin America, the Middle East, Africa and South East Asia enable us to combine the expertise of high growth companies with our own unique local knowledge and technology to ensure that our customers have access to the best financial services.
India is the biggest market for PayU globally and the company has already invested $400 million in this region in last 4 years. PayU in its next phase of growth is developing a full regional fintech ecosystem providing multiple digital financial services in one integrated experience. We are going to do this through 3 mechanisms: build, co-build/partner; select strategic investments.
PayU supports over 350,000+ merchants and millions of consumers making payments online with over 250 payment methods and 1,800+ payment specialists. The markets in which PayU operates represent a potential consumer base of nearly 2.3 billion people and a huge growth potential for merchants.

Job responsibilities:

• Design infrastructure for data, especially for but not limited to consumption in machine learning applications
• Define database architecture needed to combine and link data, and ensure integrity across different sources
• Ensure performance of data systems for machine learning to customer-facing web and mobile applications using cutting-edge open source frameworks, to highly available RESTful services, to back-end Java based systems
• Work with large, fast, complex data sets to solve difficult, non-routine analysis problems, applying advanced data handling techniques if needed
• Build data pipelines, includes implementing, testing, and maintaining infrastructural components related to the data engineering stack.
• Work closely with Data Engineers, ML Engineers and SREs to gather data engineering requirements to prototype, develop, validate and deploy data science and machine learning solutions

Requirements to be successful in this role:

• Strong knowledge and experience in Python, Pandas, Data wrangling, ETL processes, Spark statistics, data visualization, Data Modelling and Informatica.
• Strong experience with scalable compute solutions such as in Kafka, Snowflake
• Strong experience with workflow management libraries and tools such as Airflow, AWS Step Functions etc.
• Strong experience with data engineering practices (i.e. data ingestion pipelines and ETL)
• A good understanding of machine learning methods, algorithms, pipelines, testing practices and frameworks
• B. Tech / BE /MEng/MSc/PhD degree in computer science, engineering, mathematics, physics, or equivalent (preference: DS/ AI)
• Experience with designing and implementing tools that support sharing of data, code, practices across organizations at scale