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Open nowPosted today

Senior Data Engineer – Banking/Financial

MyCareersFuture92,121 open roles

Pay
SGD 10,000 – SGD 13,000 a Monthly
Where
East, Singapore
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Your applicationOpen nowSenior Data Engineer – Banking/FinancialMyCareersFuture · East, Singapore

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The clock on this job

Early applications get read.

8.0% of postings close within 7 days. Measured by our own scanner across the market. MyCareersFuture postings stay open a median of 3 days.

Share of postings closed within
  1. 1.6%1 day
  2. 3.6%3 days
  3. 8.0%7 days
  4. 15.0%14 days
  5. 34.2%30 days
This job: posted today

MyCareersFuture median: 3 days open

The posting

Job Summary

Lead the design and implementation of large-scale data engineering solutions within banking environments. Drive data platform modernization, migration, and regulatory initiatives while managing technical teams and collaborating with stakeholders to ensure robust, high-quality data delivery.

Responsibilities

  • Design and implement large-scale data pipelines, ETL frameworks, and batch processing solutions to support enterprise data platforms.
  • Develop and optimize data integration processes using Python, PySpark, SQL, Hadoop HDFS, Spark, Hive, and Teradata technologies.
  • Lead Teradata-to-Hadoop/Data Lake migration projects, legacy platform modernization, technology refresh, and application decommissioning efforts.
  • Manage and optimize enterprise ETL platforms such as Talend, DataStage, or Informatica, including migration and performance tuning.
  • Apply data modeling, profiling, quality assurance, lineage tracking, and transformation techniques on large structured and unstructured datasets.
  • Provide technical leadership to large data engineering teams through solution design, code and design reviews, troubleshooting, delivery governance, and production support.
  • Design data architecture frameworks, CI/CD pipelines, and orchestration workflows using Autosys, Control-M, Jenkins, and Git.
  • Oversee enterprise data migration, job optimization, capacity planning, and production/BAU support in high-volume banking environments.
  • Deliver regulatory and risk-data initiatives aligned with AML, Fraud, MAS regulations, BCBS239, data quality, and critical data element lineage requirements.
  • Manage stakeholder relationships with banking technology teams, business analysts, infrastructure, data management, and senior clients to ensure successful technical solution delivery.

Required competencies and certifications

  • Hands-on expertise in Python, PySpark, SQL, Hadoop HDFS, Spark, Hive, and Teradata technologies.
  • Experience with enterprise ETL platforms such as Talend, DataStage, or Informatica.
  • Proven technical leadership of large data engineering teams.
  • Experience in Teradata-to-Hadoop/Data Lake migration and legacy platform modernization.
  • Experience delivering regulatory or risk-data initiatives including AML, Fraud, MAS regulatory requirements, BCBS239, and data quality.

Preferred competencies and qualifications

  • Experience within Banking/Financial Services, especially Retail Banking, Cards, AML, Fraud, Regulatory Reporting, or Data Warehouse environments.
  • Strong stakeholder management skills with cross-functional teams and senior client stakeholders.
  • Experience designing CI/CD pipelines and orchestration using Autosys, Control-M, Jenkins, and Git.
  • Experience with performance tuning, job optimization, capacity planning, and production/BAU support in high-volume banking environments.
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