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Toss

Fintech super-app for payments and banking

Data Analytics Engineer - Platform

Data Management +1Confirmed live in the last 24 hours
Full-timeSeoul, South KoreaNo salary listedIn-person

About the Job

Requirements

  • Understand database normalization and fundamental data warehouse characteristics: subject-oriented, integrated, non-volatile, and time-variant.
  • Define key concepts clearly and design and propose efficient data structures based on understanding data from diverse perspectives as a data warehouse modeler.
  • Have a strong understanding of data warehouse standard management and be able to propose and lead improvements to enterprise-wide standards.
  • Have a strong understanding of data governance, including data quality and compliance, and be able to propose actionable plans.
  • Have strong SQL skills and be able to write efficient, readable queries.
  • Python proficiency at a beginner level sufficient to use Airflow is acceptable; familiarity with other people's modules or PySpark code is desirable.
  • Experience with large-scale data processing and designing and analyzing metrics from an AARRR perspective is desirable.
  • Experience in data warehouse implementation projects and data mart design is desirable.
  • Be able to describe specific contributions and learning from resolving data-related problems.

Responsibilities

  • After onboarding on Toss data warehouse standards, perform work as part of the Data Mart Platform Team.
  • Maintain enterprise-wide data warehouse standards that are agile and easy to manage, and collaborate with domain data analytics engineers to take responsibility for enterprise-wide data warehouse quality management, including developing and conducting standard-management monitoring.
  • Plan and execute systems and processes to improve data reliability, including improving table consistency, enhancing data quality rules, and developing health-check metrics.
  • Develop enterprise-wide data marts for investor relations, finance, and unified product analytics; integrate domain-standard marts with enterprise-wide integrated marts and improve data pipelines to enable efficient integration.
  • Identify and carry out improvements such as data discoverability so data flows effectively across the organization.
  • Develop a platform to measure data maturity across Toss domains and identify and advance projects that improve domain data analytics engineers' productivity.
  • Use a development environment based on Hadoop, Airflow, Python, and SQL (Impala).

Desired Qualifications

  • Experience with large-scale data processing and designing and analyzing metrics from an AARRR perspective.
  • Experience in data warehouse implementation projects and data mart design; describe specific contributions.
  • Describe specific problems considered and addressed in relation to data maturity.

About the Company

Toss

Fintech super-app for payments and banking

Toss is a South Korean financial services platform that started as a peer-to-peer money transfer service and has grown into a digital 'super app' for personal finance. Its products are accessed through one mobile interface that unifies bank accounts, credit cards, loans, investments, and other financial services, including its own Toss Bank and Toss Securities. It differentiates itself by offering a broad, integrated ecosystem—combining digital banking, asset management, and brokerage services under one roof and running its own banking and securities units. Its goal is to become the leading consumer finance platform in South Korea while expanding its user base globally.

Company size
1,001-5,000
Company stage
Series G
Total funding
$1.5B
Headquarters
Seoul, South Korea
Founded
2011

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