Senior Data Engineer - Enterprise Banking Data Platforms

IMPACT AI TECHNOLOGIES PTE. LTD.

Singapore

On-site

SGD 150,000 - 190,000

Full time

3 days ago

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Qualifications

Minimum 10 years of relevant experience in Data Engineering.
Bachelor’s degree in Computer Science, Engineering, Information Technology, or a related discipline
Preferred Certifications: Teradata, Cloudera, Databricks, Cloud Data Engineering, or Terraform
Core Technologies: Teradata, Hadoop/Cloudera, Spark, Hive, Impala, HBase, SQL, Python, Scala/Java, Kafka, Airflow, and Denodo.
Infrastructure & DevOps: Terraform, Kubernetes/OpenShift, Git, and CI/CD automation tools.
Domain Expertise: Enterprise banking data (Customer, Payments, Risk, Finance, AML, and Regulatory Reporting) with a strong focus on data quality, reconciliation, lineage, and historical reconstruction.
Core Competencies: Demonstrated technical leadership, disciplined delivery in regulated settings, exceptional communication skills, and accountability for production-ready outcomes.

Responsibilities

Architecture & Development: Lead the design and implementation of scalable batch, streaming, and API-based data pipelines, historical-data processing frameworks, SCD/CDC mechanisms, and semantic-layer data products.
Performance & Optimization: Optimize complex SQL queries, Spark workloads, partition strategies, and storage frameworks for large-volume processing within regulated enterprise banking environments.
Infrastructure & Automation: Implement infrastructure-as-code using Terraform and establish automated CI/CD pipelines, containerized deployments, and rigorous testing standards.
Leadership & Collaboration: Drive code reviews, enforce engineering standards, mentor junior engineers, and partner closely with architects, product teams, DevOps, and business stakeholders.

Skills

Data engineering

Leadership

Mentoring

Communication

SQL

Python/Scala

Spark

Cloud data platforms

Terraform

Education

Bachelor's degree in Computer Science/Engineering/IT

Tools

Teradata

Hadoop/Cloudera

Spark

Hive

Impala

HBase

SQL

Python

Scala/Java

Kafka

Airflow

Denodo

Databricks

Terraform

Kubernetes/OpenShift

Git

CI/CD

Job description

About the Role

We are seeking a Senior Data Engineer with deep expertise in enterprise data platforms, banking domains, and large-scale data delivery. In this role, you will lead the design and development of robust data pipelines across Teradata, Hadoop/Cloudera, and cloud ecosystems while mentoring engineering talent and driving technical excellence.

Key Responsibilities

Architecture & Development: Lead the design and implementation of scalable batch, streaming, and API-based data pipelines, historical-data processing frameworks, SCD/CDC mechanisms, and semantic-layer data products.
Performance & Optimization: Optimize complex SQL queries, Spark workloads, partition strategies, and storage frameworks for large-volume processing within regulated enterprise banking environments.
Infrastructure & Automation: Implement infrastructure-as-code using Terraform and establish automated CI/CD pipelines, containerized deployments, and rigorous testing standards.
Leadership & Collaboration: Drive code reviews, enforce engineering standards, mentor junior engineers, and partner closely with architects, product teams, DevOps, and business stakeholders.

What You Will Need to Succeed

Minimum 10 years of relevant experience in Data Engineering
Education: Bachelor’s degree in Computer Science, Engineering, Information Technology, or a related discipline
Preferred Certifications: Teradata, Cloudera, Databricks, Cloud Data Engineering, or Terraform
Core Technologies: Teradata, Hadoop/Cloudera, Spark, Hive, Impala, HBase, SQL, Python, Scala/Java, Kafka, Airflow, and Denodo.
Infrastructure & DevOps: Terraform, Kubernetes/OpenShift, Git, and CI/CD automation tools.
Domain Expertise: Enterprise banking data (Customer, Payments, Risk, Finance, AML, and Regulatory Reporting) with a strong focus on data quality, reconciliation, lineage, and historical reconstruction.
Core Competencies: Demonstrated technical leadership, disciplined delivery in regulated settings, exceptional communication skills, and accountability for production-ready outcomes.