Data Migration ETL Engineer — Hadoop, SQL & Python

D L RESOURCES PTE LTD; Singapore; On-site; SGD 90,000 - 120,000; Full time

Job summary

D L RESOURCES PTE LTD is seeking a data engineering professional to support a strategic data migration and reporting transformation initiative in Singapore. You will analyse existing data pipelines, map legacy sources to new data marts, redevelop scripts, validate outputs and produce detailed data documentation.

Responsibilities include developing SQL scripts using Hive/Impala, building scalable data workflows with Oozie, and validating data quality across large datasets in a banking/enterprise

Qualifications

• Strong SQL, SAS or Python scripting and data manipulation skills.
• Hands-on experience with Hue, Hive, Impala, Oozie.
• Experience in data warehousing, ETL development, data migration, or data engineering.

Responsibilities

• Data Analysis & Discovery: analyze existing tables, reports, datasets, and data processing workflows.
• Source Mapping & Migration: perform source-to-target mapping and document field mappings and business logic.
• Development & Automation: develop and maintain SQL scripts and data extraction/validation processes; rebuild datasets in new data marts; automate workflows with Oozie.
• Data Validation & Testing: reconcile outputs, validate data accuracy and timeliness, support UAT.
• Documentation & Governance: create data lineage, metadata, data dictionaries, and runbooks.

Skills

SQL

SAS or Python

Data manipulation

Analytical thinking

Stakeholder communication

Education

Bachelor's degree in Computer Science or related field

Tools

Hue

Hive

Impala

Oozie

Job description

D L RESOURCES PTE LTD is seeking a data engineering professional to support a strategic data migration and reporting transformation initiative in Singapore. You will analyse existing data pipelines, map legacy sources to new data marts, redevelop scripts, validate outputs and produce detailed data documentation.

Responsibilities include developing SQL scripts using Hive/Impala, building scalable data workflows with Oozie, and validating data quality across large datasets in a banking/enterprise