FINNOMENA
FINNOMENA
201 – 500 Employees
FinanceFintechMedia
FINNOMENA is a Thai fintech company operating at the intersection of finance and media. Its platform helps individual investors research markets, follow financial news, compare mutual funds, review recommendations, and manage investment decisions. Alongside market alerts, weekly insights, fund screeners, and real-time pricing information such as gold prices, FINNOMENA supports account opening and mutual fund purchases, including access to funds it manages. The company brings investment content, research tools, and fund distribution into one service for retail investors.

Associate Data Analytics Engineer – FINNOMENA, Hybrid Thailand

Associate Data Analytics Engineer responsible for SQL, Python, and PySpark pipelines, with a focus on Google Cloud ingestion, data quality, monitoring, and analytics support.

Description

  • Build and maintain assigned batch ETL and ELT workflows with SQL, Python, and PySpark
  • Support ingestion from databases, APIs, files, and Google Workspace sources
  • Apply foundational data cleansing, transformation, and source-to-target validation
  • Contribute to streaming pipeline development and maintenance with Google Cloud Pub/Sub and Datastream
  • Create and maintain checks for missing, duplicate, invalid, and delayed data
  • Track batch and streaming workflows, data freshness, and overall pipeline health
  • Inspect logs, resolve routine problems, and escalate more complex incidents
  • Support authorized pipeline reruns and data reprocessing activities
  • Assemble datasets for downstream analytics and reporting use
  • Help maintain dashboards that track pipeline status and data quality
  • Record data mappings, transformation logic, validation criteria, and troubleshooting procedures
  • Work with Git and take part in code reviews and pre-release testing

Requirements

  • Open to recent graduates and candidates with up to two years of relevant experience
  • Working knowledge of SQL, Python, and PySpark
  • Capability to build and maintain batch ETL and ELT workflows
  • Capability to support ingestion from databases, APIs, files, and Google Workspace sources
  • Understanding of data cleansing, transformation, and source-to-target validation practices
  • Ability to contribute to streaming pipelines built with Google Cloud Pub/Sub and Datastream
  • Ability to create and maintain data quality checks
  • Ability to monitor pipelines, inspect logs, and resolve routine issues
  • Ability to document data mappings, transformation logic, validation criteria, and troubleshooting procedures
  • Experience with or familiarity with Git, code reviews, and software testing
  • Familiarity with Google Cloud services such as BigQuery, Dataform, Google Cloud Storage, Managed Service for Apache Airflow, Managed Service for Apache Spark, Pub/Sub, and Datastream

Benefits

  • Practical experience working with the team’s Google Cloud data platform
  • Mentorship and code review support from experienced colleagues

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