Enterprise Data Lake Systems Analyst

UARROW PTE. LTD.; Singapore; On-site; SGD 90,000 - 130,000; Full time

Job summary

UARROW PTE. LTD. in Singapore is seeking an experienced Data Engineer to design, integrate and support enterprise-scale data platforms and data-lake solutions. The role focuses on building robust ETL pipelines and ensuring data reliability across the organization.

You will optimize SQL and ETL workflows, coordinate with cross‑functional teams, and implement data-quality, metadata and governance controls to support SIT/UAT and production validation.

Responsibilities

• Design and enhance enterprise data integration and Data Lake solutions.
• Develop and optimize ETL workflows using Informatica, DataStage and SQL.
• Perform source-to-target mapping, data transformation, reconciliation and validation.
• Work with Hadoop, Hive, Impala, Teradata, Oracle and Netezza environments.
• Implement data-quality, metadata and data-governance controls.
• Analyze complex datasets and resolve data discrepancies and integration issues.
• Support SIT/UAT, production validation and technical defect resolution.
• Optimize SQL queries, ETL processes and high-volume batch workloads.
• Collaborate with technical, business and offshore/onshore teams to deliver enterprise data initiatives

Job description

We are seeking an experienced Data Engineer to design, integrate and support enterprise-scale data platforms and data-lake solutions. The role involves developing and optimizing complex ETL pipelines, integrating multiple upstream and downstream data sources, performing data transformation and reconciliation, and implementing data-quality and validation controls.

Key Responsibilities:

• Design and enhance enterprise data integration and Data Lake solutions.
• Develop and optimize ETL workflows using Informatica, DataStage and SQL.
• Perform source-to-target mapping, data transformation, reconciliation and validation.
• Work with Hadoop, Hive, Impala, Teradata, Oracle and Netezza environments.
• Implement data-quality, metadata and data-governance controls.
• Analyze complex datasets and resolve data discrepancies and integration issues.
• Support SIT/UAT, production validation and technical defect resolution.
• Optimize SQL queries, ETL processes and high-volume batch workloads.
• Collaborate with technical, business and offshore/onshore teams to deliver enterprise data initiatives