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Data Engineer / ETL Developer

Summary

Builds and maintains ETL pipelines to extract, clean, and transform enterprise data into analytics-ready datasets for reporting tools like Spotfire.

Location: Singapore (Candidate must be based in Singapore)

Duration: 12 Months

Job Responsibilities
  • Execute and maintain data extraction processes from multiple enterprise systems (e.g. P23, P62, Data Lake, Oasis, Solumina, and future platforms).
  • Work closely with application owners and Digital Technology (DT) teams to establish secure and reliable data integrations.
  • Monitor and troubleshoot data pipelines to ensure data availability and timely delivery.
  • Design, develop, and maintain ETL/ELT workflows to transform raw data into analytics-ready datasets.
  • Perform data cleansing, mapping, aggregation, and validation while maintaining data quality standards.
  • Conduct data quality checks for completeness, accuracy, and consistency, and resolve data-related issues with business stakeholders.
  • Support and maintain Spotfire reporting solutions, including upstream data processes feeding dashboards.
  • Optimize reporting performance, refresh schedules, and user access management.
  • Prepare technical documentation including data flows, ETL specifications, process documentation, and data dictionaries.
  • Ensure compliance with data governance, security, and enterprise standards.
  • Identify opportunities for automation and continuous process improvement.
Required Skills
  • Experience in ETL/ELT development and data integration.
  • Experience with data transformation, cleansing, and validation.
  • Knowledge of data pipeline monitoring and troubleshooting.
  • Experience with enterprise data warehouses or Data Lakes.
  • Familiarity with BI/reporting tools (Spotfire preferred).
  • Understanding of data governance and data quality best practices.
  • Good communication skills with the ability to work with cross-functional team.
Preferred Skills
  • Experience with TIBCO Spotfire.
  • Experience integrating data from manufacturing or enterprise applications.
  • Knowledge of automation and scripting.
  • Experience working in Digital Transformation or enterprise analytics environments.

See also