The posting
Our client, one of Asia-Pacific’s leading organizations is looking for:
Data Engineer
Responsibilities:
- Develop and maintain ETL pipelines and file-based interfaces for ingesting HR data into ODIN, including data profiling, mapping, specifications and dataset onboarding.
- Build and maintain SQL and Python logic to cleanse, standardise, transform and reconcile HR data into reliable, reusable datasets, including historical and legacy data.
- Enhance ODIN data models, tables and dependencies to meet new requirements, with traceable mappings, definitions and processing rules.
- Support CRs and SRs by reviewing requirements, executing tests, validating outputs, documenting defects and resolving issues through implementation.
- Automate validation, reconciliation and cleansing checks; investigate anomalies, trace lineage, resolve root causes and verify fixes.
- Monitor pipelines and interfaces, troubleshoot failures, perform reruns and improve reliability, performance, maintainability and operational documentation.
- Develop governed datasets, Athena tables/views and queries, and Tableau data sources/workbooks for approved reporting and analytics needs.
- Translate stakeholder requirements into data mappings, transformation rules and technical solutions, while documenting decisions and supporting timely delivery.
- Provide technical evidence for audits, access reviews and assurance activities, and support required remediation.
Requirements:
- Strong proficiency in SQL and working proficiency in Python, with hands-on experience developing data pipelines, transformations, validation and automation.
- Experience with AWS data services such as S3 ingestion, CSV/Parquet, IAM, portioning, and Athena tables, views and queries, or comparable cloud data platforms, is preferred.
- Familiarity with Spark, Databricks or similar modern data engineering technologies is advantageous but not required for the current ODIN environment.
- Hands-on understanding of ETL, data pipeline design and operations, relational and file-based data, data warehousing and data modelling.
- Able to work with complex or legacy source structures and transform them into clean, standardised and reliable datasets for downstream consumption.
- Practical experience implementing data validation and reconciliation checks, investigating discrepancies, tracing data lineage and identifying root causes across source, interface and transformation layers.
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Interested applicants can also email CV at [email protected] (for faster processing, please state the exact job / position title applied “Data Engineer"
Only shortlisted candidates will be notified.
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EA License Number: 10C3636 EA Personnel Name: Chauhan, Asmita EA Personnel Registration Number: R1980706
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