Data Engineer

KEY CONNECT RECRUITMENT PTE. LTD.; Singapore; On-site; SGD 180,000 - 240,000; Full time

Job summary

KEY CONNECT RECRUITMENT PTE. LTD. is seeking a senior Data SME to support a data engineering initiative built on Azure and Databricks within Corporate Banking.

The role focuses on end-to-end data solutions on a live banking data platform, with emphasis on data mapping, pipeline development, and performance tuning. The ideal candidate has 10+ years in data, strong SQL and Python skills, and solid SDLC experience across requirements, design, build, test and deployment.

Qualifications

• 10+ years of experience in the data space with Corporate Banking exposure.
• Hands-on in Databricks, Azure, SQL, and Python.
• Experience across SDLC phases: requirements, design, build, test, and deployment.
• Strong understanding of data warehouse concepts (e.g., dimensional modeling, ETL/ELT).
• Excellent communication and ownership of a live data platform.
• Experience with integration methods: FTP/SFTP, MQ, and APIs.

Responsibilities

• Own data solutions end-to-end on a live banking data platform.
• Lead pipeline development and performance tuning on Databricks.
• Collaborate across SDLC phases and stakeholder groups.

Skills

Databricks

Azure

SQL

Python

Data mapping

SDLC

Data warehouse concepts

ETL/ELT

Job/cluster management

Performance tuning

APIs

FTP/SFTP

MQ

Tools

Databricks

Azure

Job description

We are looking for a senior Data SME to support a data engineering initiative built on Azure and Databricks within a Corporate Banking context. The ideal candidate brings deep, hands-on technical experience in data mapping and the

Databricks platform, strong SDLC and data warehouse fundamentals, and is comfortable owning data solutions end-to-end on a live banking data platform. Trade, Lending, or Payment domain exposure is a strong plus.

Required Skills & Experience

• At least 10 years of experience in the data space, with exposure to Corporate Banking.
• Technically strong in data mapping (source-to-target) and the Databricks platform - pipeline development, job/cluster management, and performance tuning.
• Strong experience across SDLC phases: requirements, design, build, test, and deployment.
• Strong understanding of data warehouse concepts (e.g., dimensional modeling, ETL/ELT).
• Strong working knowledge of Azure and Databricks.
• Strong hands-on SQL and Python skills.
• Working knowledge of integration methods: file transfer protocols (FTP/SFTP), MQ, and APIs.
• Excellent communication skills and proven hands-on ownership of a live data platform.

Good to Have

• Trade, Lending, or Payment domain exposure.
• Prior experience on a core banking or banking transformation program.