Data Engineer / データエンジニア

PayPay; India; Hybrid; INR 1,500,000 - 2,800,000; Full time

Benefits offered by this job

Visa sponsorship

Relocation support

Job summary

PayPay is seeking a Data Engineer in India to design, build, and operate scalable data pipelines on AWS, Databricks, and Lakehouse architectures. You will collaborate with product, analytics, risk, and security teams to support data-driven features for a next-generation digital financial platform.

The ideal candidate has 4+ years of experience building data lakes and warehouses, strong Python/SQL skills, and hands-on experience with Airflow, Terraform, and streaming technologies such as Kafka.

Qualifications

• 4+ years of professional experience as a Data Engineer or related role.
• Hands-on experience designing, building, and operating data lakes, data warehouses, or data lakehouse platforms.
• Experience processing large-scale datasets with Databricks, Delta Lake, or Apache Spark.
• Strong development skills in Python, PySpark, SQL.
• Experience with workflow orchestration tools such as Airflow, Dagster, or Prefect.
• Experience operating cloud-based systems on AWS.
• Experience with Infrastructure as Code (Terraform).
• Knowledge of data governance, metadata management, and data cataloging.

Responsibilities

• Design, develop, and operate robust data ingestion pipelines using Databricks, AWS DMS, and Terraform.
• Develop large-scale data processing workflows with Spark, Python, and SQL.
• Build data integration platforms connecting banking services, payments, and internal data sources.
• Optimize pipelines using CDC, streaming, and batch processing architectures.
• Build and maintain data lakehouse and data catalog platforms (Databricks Lakehouse, Unity Catalog).
• Implement data governance: quality, lineage, access control, auditing.

Skills

Databricks

AWS

Python

SQL

Airflow

Dagster

Prefect

Terraform

Kubernetes

Data Lakehouse

Unity Catalog

Tools

Databricks

Airflow

Terraform

Kubernetes

Unity Catalog

AWS Lake Formation

Job description

PayPay is a FinTech company that has grown to over 75M (as of August 2026) users since its launch in 2018. Our team is hugely diverse with members from over 50 different countries.

OUR VISION IS UNLIMITED_

We dare to believe that we do not need a clear vision to create a future beyond our imagination. PayPay will always stay true to our roots and realize 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. We are looking for people who can embrace this challenge, refresh the product at breakneck speed and promote PayPay with professionalism and passion. Please note that you cannot apply or be selected in parallel with PayPay Corporation, PayPay Card Corporation and PayPay Securities Corporation.

OUR VISION IS UNLIMITED_

The assigned organization is primarily advancing projects related to a next-generation digital financial platform. Our team takes the lead in designing, building, and operating modern data engineering infrastructure from scratch to enable data-driven innovation across the group.

As the business continues to grow rapidly, the importance of data utilization across both PayPay Bank and the broader PayPay Group is increasing. To support product enhancements, marketing initiatives, and fraud detection, establishing a robust data engineering foundation that delivers high reliability, security, and scalability is an urgent task.

• Design, develop, and operate robust and scalable data ingestion pipelines using technologies such as Databricks, AWS DMS, and Terraform
• Develop large-scale data processing workflows using Spark, Python, and SQL
• Design and build data integration platforms that connect banking services, payment systems, internal business applications, and external data sources
• Optimize data pipelines by combining Change Data Capture (CDC), streaming, and batch processing architectures
• Build and maintain data lakehouse and data catalog platforms leveraging Databricks Lakehouse and Unity Catalog
• Design and operate data governance capabilities, including data quality management, metadata management, data lineage, access control, and audit logging
• Improve performance, optimize costs, and enhance reliability for large-scale data processing environments
• Implement SRE and observability practices for data platforms, including monitoring, alerting, dashboards, and incident response
• Build, automate, and standardize data infrastructure using Infrastructure as Code (IaC) technologies such as Terraform
• Develop and maintain shared frameworks, tools, templates, and CI/CD pipelines to improve the efficiency and consistency of data engineering operations
• Partner with product, analytics, risk management, security, compliance teams, and other PayPay Group companies to drive data utilization and business value
• Operate and enhance data platforms in compliance with the security, privacy, regulatory, and internal control requirements expected of a financial institution
• Cloud: AWS
• Orchestration: Airflow, Dagster, Prefect
• Streaming / Ingestion: Kafka, CDC tools
• Infrastructure: Terraform, GitOps, CI/CD
• Governance: Unity Catalog, AWS Lake Formation, Data Catalog, Metadata Management
• At PayPay Bank, Data Engineers do far more than simply collect and process data. This role is about building the data foundation that powers the next generation of digital financial services by combining the reliability and trust required of a bank with the speed, scale, and user reach of the PayPay Group.
• You will have the opportunity to drive data-enabled innovation that directly supports product development and business growth, while meeting the stringent security, governance, compliance, and auditability requirements expected of a financial institution. Leveraging modern data technologies such as Databricks and Lakehouse architectures, you will help establish a scalable and trusted data platform that enables the organization to make better decisions and deliver better customer experiences.
• PayPay Bank’s strengths lie in its ability to develop products in‑house from concept through implementation, its marketing capabilities that deliver value to tens of millions of users, and its robust financial and corporate foundations that maintain the trust expected of critical social infrastructure. As a Data Engineer, you will play a key role in supporting these strengths across the organization and contribute to the challenge of redefining what a bank can be in the digital era.
• 4+ years of professional experience as a Data Engineer, Data Platform Engineer, or in a related role
• Hands‑on experience designing, building, and operating data lakes, data warehouses, or data lakehouse platforms
• Experience processing large-scale datasets using one or more of the following technologies: Databricks, Delta Lake, or Apache Spark
• Strong development experience using Python, PySpark, SQL, or related technologies
• Experience with workflow orchestration tools such as Airflow, Dagster, or Prefect
• Experience developing and operating cloud-based systems on AWS
• Experience building and managing infrastructure using Infrastructure as Code (IaC) tools such as Terraform
• Proven experience designing and improving large-scale data pipelines with a focus on performance, reliability, availability, and operational excellence
• Business‑level Japanese proficiency (native‑level or equivalent to JLPT N1/N2)
• Experience building and operating data platforms within financial domains such as banking, fintech, payments, credit, securities, or insurance
• Experience with event‑driven data architectures and streaming data processing using technologies such as Kafka
• Experience with Change Data Capture (CDC) tools such as Canal, Debezium, or Maxwell
• Experience with data cataloging, access management, and metadata management solutions such as Unity Catalog or AWS Lake Formation
• Experience improving monitoring and observability using tools such as Prometheus, Grafana, Datadog, or Amazon CloudWatch
• Experience designing, building, and operating CI/CD pipelines using tools such as GitHub Actions or Jenkins
• Experience operating cloud‑native platforms using Kubernetes, Amazon EKS, Argo CD, or related technologies
• Experience with data quality management, data lineage, data contracts, and master data management (MDM)
• Experience designing access controls, encryption, data masking, and audit logging for systems handling personal data, sensitive information, or financial transaction data
• Experience establishing data engineering standards, development guidelines, shared libraries, and engineering best practices
• Experience leading engineering teams, driving technology selection, conducting architecture reviews, and mentoring engineers
• Proven experience integrating AI‑assisted development practices into system design, software development, and delivery processes
• Contributions to AI‑related open‑source projects and/or experience building workflow automation solutions powered by AI technologies
• You are passionate about building user‑first financial services and share our commitment to creating better financial experiences for customers
• You view data platforms as products and are motivated to improve the productivity and experience of their users, including data engineers, analysts, business teams, and product teams
• You can balance the reliability, resilience, and trust required of a financial institution with the speed and agility expected of a fintech company
• You think beyond immediate tasks and are able to design architectures and operational models that scale sustainably over the long term
• You are comfortable tackling complex challenges, forming hypotheses, driving initiatives independently, and collaborating with stakeholders to achieve outcomes
• You see security, governance, and compliance not as constraints, but as essential foundations for enabling trusted and effective data utilization
• You are committed to continuous learning, actively explore new technologies, and enjoy sharing knowledge and best practices with your team and the broader organization
• Hybrid Workstyle
• In principle, 9:00am-5:45pm + 1h break (actual working hours: 7h45m + 1h break)

Holidays

Every Sat/Sun/National holidays (In Japan)/New Year's break/Company-designated Special days

Paid leave

• Annual leave (up to 14 days in the first year, granted proportionally according to the month of employment. Can be used from the date of hire)
• Personal leave (5 days each year, granted proportionally according to the month of employment）PayPay's own special paid leave system, which can be used to attend to illnesses, injuries, hospital visits, etc., of the employee, family members, pets, etc.
• Annual salary paid in 12 installments (monthly)
• Based on skills, experience, and abilities
• Reviewed once a year
• Late overtime allowance
• Payroll payment can be changed to digital salary payment “PayPay Paycheck” for an amount set by you
• Social Insurance (health insurance, employee pension, employment insurance and compensation insurance)
• 401K
• Translation/Interpretation support
• VISA sponsor + Relocation support