Senior Data Engineer - Banking/Financial

RISKDATA CONSULTING PTE. LTD.; Singapore; On-site; SGD 120,000 - 180,000; Full time

Job summary

RISKDATA CONSULTING PTE. LTD. seeks a senior data engineering leader to design and implement large-scale data pipelines within banking environments.

You will drive data platform modernization, migration, and regulatory programs while guiding technical teams and coordinating with stakeholders to ensure robust, high-quality data delivery. The role requires hands-on Python/PySpark/SQL, experience with ETL tools (Talend/DataStage/Informatica), and leadership across Teradata-to-Hadoop migrations.

Qualifications

• Hands‑on Python, PySpark, SQL, Hadoop HDFS, Spark, Hive, and Teradata expertise.
• Experience leading large data engineering teams.
• Experience with Teradata-to-Hadoop/Data Lake migrations and legacy modernization.

Responsibilities

• Design and implement large-scale data pipelines and batch processing for enterprise data platforms.
• Lead data platform modernization, migration, and regulatory initiatives in banking environments.
• Provide technical leadership: code reviews, troubleshooting, governance, and production support.
• Oversee CI/CD pipelines and orchestration using Autosys, Control-M, Jenkins, and Git.
• Manage data migration, job optimization, capacity planning, and high-volume production support.

Skills

Python/PySpark/SQL

Data engineering leadership

Regulatory data initiatives

Teradata migration to Hadoop/Data Lake

CI/CD orchestration (Autosys/Control-M

Jenkins/Git for delivery

Tools

Talend

DataStage

Informatica

Autosys

Control-M

Jenkins

Git

Hadoop/HDFS

Teradata

Spark/Hive

Job description

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.