Junior Data Engineer (Software Engineering Focus) - Fintech Startup

★Junior Data Engineer | Featured Fintech Startup

• Business Japanese REQUIRED

★Hybrid Work

★Own Products/Services

★Life Support & Learning Support

★Annual salary: 7.5 million yen - 10 million yen

-------------【About the company】-------------

A University of Tokyo-born startup leveraging big data and generative AI to support data utilization and digital transformation (DX), primarily for major enterprises.

The company operates businesses that support corporate decision-making by utilizing various alternative data—such as credit card data, POS data, and location data—as well as businesses that facilitate decision-making across society through data infrastructure construction support and generative AI development.

■Services & Solutions Offered

・Institutional Investor Analytics: Data analytics services utilizing POS and credit card transaction data.

・JCB Consumption Trend Index: Industry-by-industry consumer spending indicators built on JCB card payment data.

・Nikkei Daily Price Index: Daily inflation and price tracking metrics powered by Nikkei POS data.

・HRog Recruitment & Wage Indices: Job posting and offered wage indices derived from HRog recruitment advertising data.

・Commercial Real Estate DX Services: Data utilization and digital transformation solutions tailored for commercial real estate.

・Enterprise DX Solutions: AI- and data-driven end-to-end DX implementation services for corporate clients.

・Public Sector & Local Government Solutions: Analytics and Generative AI-powered solution services for public administration and municipal entities.

・Led by a "Snowflake Data Superhero":

The company's technology strategy is spearheaded by its VP of Data & AI, who holds the prestigious "Snowflake Data Superhero" designation—a globally recognized elite tech leader status awarded to only 128 individuals worldwide (and just 15 in Japan) for FY2026.

-------------【 Job Description】-------------

【Services Offered by the Company】

・Analytical services for institutional investors utilizing POS and credit card data

・Industry-specific consumption trend indices leveraging JCB card transaction data

・Daily price index using Nikkei POS data

・Recruitment wage and job opening indices using HRog job advertisement data

・Service suites supporting data utilization and DX tailored for commercial real estate

・Solution services supporting corporate DX driven by data and generative AI

・Data analytics and generative AI solution services for local governments and public sector agencies

■Engineering Environment Powered by a "Snowflake Data Superhero"

The company counts among its team a "Snowflake Data Superhero"—an officially recognized technology leader, chosen as one of only 128 individuals globally and 15 in Japan for FY2026.

■World-Class Technical Expertise & Insights

A top-tier data engineer, recognized for deep technical mastery and community contributions among a select group of 128 data experts worldwide, leads the company's overall data strategy.

■Culture of Knowledge Sharing

Selection as a "Snowflake Data Superhero" requires not only exceptional technical capability but also selfless knowledge sharing through technical blogging and speaking engagements. This spirit of generously giving back insights to team members defines the company’s engineering culture, creating one of Japan’s premier learning environments where engineers can receive direct code and design reviews from industry pioneers.

■An Organization That Respects & Supports Individual Challenges

The company views engineers' external activities and continuous learning as indispensable investments in organizational growth. Engineers take center stage within an open environment that fully respects and supports their ambitions.

【Recruitment Background】

In recent years, the data services market has expanded rapidly at a compound annual growth rate (CAGR) of approximately 18.15%, driving unprecedented demand for data engineers in the AI era.

Within this high-growth sector, the company is redefining data platforms through a software engineering lens, actively promoting the "productization of data infrastructure as software." Consequently, the design skills, engineering rigor, and quality-first mindset cultivated as a software engineer are critical to advancing modern data engineering.

In this role, the company seeks individuals who can apply their software engineering experience in system design, quality assurance, and operational excellence toward building and managing scalable data platforms and pipelines

【Your Role】

As a Software Engineer, you will engage in development that supports the company's internal products and client-facing solutions, focusing on data platforms, data pipelines, and data quality.

The role requires pursuing data engineering outcomes using modern software engineering best practices—including implementation (batch, workflow orchestration, IaC), testing and CI, monitoring and incident response, as well as schema design and performance optimization. Depending on your experience and interests, the scope can be expanded to include data analytics, core product development, or generative AI initiatives.

Note: The specific team assignment will be determined through mutual discussion, taking into account the candidate's background, strengths, and career preferences.

【Responsibilities】

・Designing, building, testing, developing, maintaining, and operating data platforms (including code reviews and release management processes).

・Architecting, developing, and managing data pipelines for in-house products and analytics services.

・Providing customer implementation support for generative AI adoption (hands-on technical areas such as data connectivity, data governance, and evaluation infrastructure).

【How Your Experience Will Be Leveraged】

・System design and development skills built as a software engineer directly translate to the emerging paradigm of "data infrastructure as software."

・System design insights gained from microservices architectures can be applied directly to Data Mesh and Lakehouse designs.

・Experience with Test-Driven Development (TDD) and CI/CD pipelines enables automated testing, continuous integration, and rigorous quality assurance across data pipelines.

・Database tuning experience can be leveraged for query optimization, performance engineering, and scaling enterprise DWH environments.

・Logical reasoning, code readability, and maintainability practices developed through software engineering directly improve data quality, pipeline reproducibility, and schema design.

【Position Highlights】

・Leverage existing software engineering experience to gain high-demand expertise at the intersection of software engineering and modern data systems.

・Work end-to-end—from architectural design to hands-on implementation—using cutting-edge technologies including Snowflake, dbt, Airflow, Terraform, and major cloud providers (AWS, Google Cloud, Azure).

・Transform hands-on engineering execution capabilities into high-value expertise that directly empowers data-driven decision-making across organizations.

・Position data at the core of product and business strategy to drive tangible enterprise outcomes.

・Gain direct experience with cutting-edge initiatives, including real-time analytics, AI integration, and personalization systems.

-------------【 Requirements】-------------

Required

Experience in system development and operations as part of a team

Experience in development and operations using Python, Go, and other languages

Development experience as a server-side engineer or infrastructure engineer

Preferred

Experience in face-to-face negotiations (client communication)

Experience using ETL tools such as dbt, Dataform, and Glue

Experience using workflow management tools such as Airflow

Knowledge of data management, as represented by the DMBOK

Ability to build and manage public cloud resources (e.g., AWS) using IaC tools such as Terraform

Development experience using container technologies such as Docker

Ideal Applicants

A desire to apply software engineering capabilities to solve complex data infrastructure challenges.

Driven to support product and service development from the ground up through robust data platform engineering.

Proactive in adopting emerging technologies and disseminating best practices across the organization.

Ability to work effectively across department boundaries to drive problem-solving initiatives.

A strong sense of accountability toward data quality, system reproducibility, and operational transparency.

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【Working Time 】

10:00～19:00

【 Welfare 】

・Full social insurance

・Incentive (trust-type SO) system available

・Commuting allowance

・Visa support

・No smoking indoors

Life Support

・Marriage leave and congratulatory money: Special paid leave (7 days) and congratulatory money (50,000 yen) are provided for marriages.

・Parental leave and congratulatory money: Special paid leave (5 days) and congratulatory money (500,000 yen per baby!) for the birth of a child. (500,000 yen per baby!!!)) are provided for the birth of a child.

・Support for congratulatory and mourning occasions: Special paid leave (3 to 7 days) is provided for marriage, childbirth, and of course, in case of any misfortunes that may occur.

・Consecutive vacation days: In addition to paid leave, employees are allowed to take 5 consecutive days off.

・Allowance for dependents: Up to 100,000 yen per month per person depending on the number of children before elementary school age

【 Holiday 】

・Saturday/Sunday/National Holiday

・Annual Paid Leave

・New Year Holiday

・Parental Leave

・Congratulations & Condolence Leave

・Summer Holiday

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