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Toss

Fintech super-app for payments and banking

Data Engineer – Financial Data/Finance

Data EngineeringConfirmed live in the last 24 hours
Full-timeSeoul, South KoreaNo salary listedIn-person

About the Job

Requirements

  • At least 3 years of hands-on data engineering experience; financial data processing experience is preferred.
  • Ability to collect and process data using Python and SQL.
  • Experience designing and implementing data collection systems that integrate external APIs and files.
  • Experience developing and operating batch pipelines such as Airflow.
  • Experience processing data in RDBMS and distributed data environments such as Impala, ClickHouse, and Kafka.
  • Understanding of the financial data domain and experience transforming complex source data into useful investment information assets.
  • Experience tracing data consistency and quality issues to their root causes in data structure and domain context, rather than only correcting errors.

Responsibilities

  • Build pipelines to collect, process, and load data from domains such as domestic and international disclosures, earnings, economic indicators, and market prices; handle operational work including incident response, backfills, and monitoring.
  • Structure unstructured source data such as disclosures using LLMs to create investment information assets, and continue exploring new technologies.
  • Analyze specifications from external vendors such as Refinitiv (LSEG), S&P Global, and FnGuide; map them to internal standard data models and establish criteria to reconcile differences between vendors.
  • Map vendor-specific security identifiers such as tickers, ISIN, and RIC to internal standard identifiers, and manage events such as ticker changes, delistings, and corporate actions.
  • Develop pipelines to calculate quantitative factors from financial and price data, and validate calculation logic for accuracy.
  • Explore and analyze large volumes of investment information to detect outliers and identifier-mapping errors, and build data-quality systems that validate consistency, completeness, and timeliness between source and processed data.
  • Analyze source-data structures and business meaning, and take responsibility for the end-to-end standardization process, including pipeline construction, identifier mapping, and defining data models and quality standards.

Desired Qualifications

  • Experience comparing and integrating data from multiple financial vendors, or designing its use in financial services.
  • Experience developing services in JVM languages such as Kotlin or Java.
  • Experience deploying and operating services in Kubernetes environments.
  • Practical experience applying LLM or other AI technologies to pipelines that structure unstructured disclosure data.
  • Experience implementing pipeline logic to calculate investment indicators (quantitative factors) from financial and market-price data.
  • Experience integrating AI development tools such as Claude Code or Cursor into development and operations workflows.
  • Experience processing financial data is preferred.

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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