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Senior Data Engineer

SpringCube

Full time - Senior Engineer

Fintech

Singapore, All Areas

Published 2 weeks ago

Salary: Disclosed upon interview

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Job Description

The SpringCube team curated the following job opportunity to help you in your job search. Explore the position below to find your next career move.

Company Overview
A global payments and financial technology organization provides a unified platform for businesses worldwide. The company empowers over 200,000 businesses with integrated solutions for accounts, payments, spend management, treasury, and embedded finance. With a team of 2,000+ technology professionals across 26 offices globally, the organization is valued at US$8 billion and backed by leading investors, delivering innovative solutions in global banking and financial operations.

About the Role
The Senior Data Engineer will design, build, and maintain scalable data infrastructure that supports business intelligence, machine learning, and operational workflows. This role contributes to data modeling, pipeline management, data governance, and AI integration, ensuring high-quality, reliable, and actionable data across the company.

Responsibilities

Data Modeling

  • Design and implement robust, scalable data models for BI, ML, and operational requirements
  • Select and apply appropriate schema designs (e.g., star schema, snowflake, normalized/denormalized)
  • Collaborate with business teams to translate data needs into clean, structured, well-documented models
  • Promote Single Source of Truth (SSOT) principles across data layers
  • Ensure consistency, traceability, and quality across multiple data sources and domains

ETL and Data Pipeline Management

  • Build and maintain batch and streaming ETL pipelines
  • Manage end-to-end data workflows, from ingestion to transformation and delivery
  • Collaborate with Data Platform Engineers and Product Managers to troubleshoot and resolve data issues
  • Handle challenges in distributed or multi-datacenter environments, including data migration, duplication, and consistency

Data Governance

  • Contribute to data governance strategies, policies, and standards
  • Support pillars of data governance including quality, stewardship, metadata, master data, privacy/security, and lifecycle management

Data + AI

  • Apply data engineering expertise to support AI and ML initiatives
  • Explore practical and creative ways to integrate AI with data workflows

Qualifications

  • Strong experience in data modeling, ETL, and data pipeline development
  • Proficiency in SQL, Python, or similar programming languages
  • Familiarity with batch and streaming data workflows
  • Understanding of distributed data systems and multi-datacenter environments
  • Knowledge of data governance principles and best practices
  • Interest in AI/ML integration with data engineering pipelines
  • Excellent problem-solving, collaboration, and communication skills

Disclaimer
SpringCube curates tech job listings from various company websites to support tech professionals in Singapore.

1. No Endorsement: Job ads on SpringCube do not imply endorsement of their authenticity or quality.
2. No Client Relationship: This company is not a client of SpringCube unless stated.
3. To Apply: Click the “Apply” button to be redirected to the hiring company’s application page for this job.
4. No Liability: SpringCube is not liable for inaccuracies.