PayPay, a fintech company providing a service enjoyed by 70 million users (as of July 2025) merely 7 years since its launch in 2018 in Japan. To build our Payment services, we got technical cooperation from Paytm (A large payment service company in India). And based on their customer-first technologies , we created and expanded the smartphone payment service in Japan. Therefore, we have decided to establish a development base in India, because it is a major IT country with many talented engineers, as evidenced by the fact that cutting-edge mobile payments can continue to be generated.
PayPay will always stay true to our roots and realise a vision (future) that no one else can imagine by constantly taking risks and challenging ourselves. With this mindset, you will be presented with new and exciting opportunities on a daily basis and have the opportunity to grow and reach new dimensions that you could never have imagined.

PayPay India is looking for a Data Engineer to work on our payment system to deliver the best payment experience for our customers. The Data Pipeline team is tasked with creating, deploying, and managing this platform, utilizing leading technologies like Databricks, Delta Lake, Spark, PySpark, Scala, and the AWS suite.
We are actively seeking skilled Data Engineers to join our team and contribute to scaling our platform across the organization.
Create and manage robust data ingestion pipelines leveraging Databricks, Airflow, Kafka, and Terraform.
Ensure high performance, reliability, and efficiency by optimizing large-scale data pipelines.
Develop data processing workflows using Databricks, Delta Lake, and Spark technologies.
Maintain and improve the Data Lakehouse, utilizing Unity Catalog for efficient data management and discovery.
Construct automation, frameworks, and enhanced tools to streamline data engineering workflows.
Collaborate across teams to facilitate smooth data flow and integration.
Enforce best practices in observability, data governance, security, and regulatory compliance

Minimum 7 years as a Data Engineer or similar role.
Hands-on experience with Databricks, Delta Lake, Spark, and Scala.
Proven ability to design, build, and operate Data Lakes or Data Warehouses.
Proficiency with Data Orchestration tools (Airflow, Dagster, Prefect).
Familiarity with Change Data Capture tools (Canal, Debezium, Maxwell).
Strong command of at least one primary language (Scala, Python, etc.) and SQL.
Experience with data catalog and metadata management (Unity Catalog, Lakeformation).
Experience in Infrastructure as Code (IaC) using Terraform.
Excellent problem-solving and debugging abilities for complex data challenges.
Leverage AI/LLM-based tools in daily workflows (e.g., code development, reviews, testing, debugging, documentation), while ensuring human oversight, judgment, and accountability drive the final product.

Data Engineer (AWS, SQL)

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