Lead Data Engineer (Teradata/Hadoop)
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Summary
A lead data engineer role in Singapore designing and building large-scale batch, streaming, and API data pipelines across Teradata, Hadoop/Cloudera, and cloud platforms for regulated enterprise banking, while mentoring engineers. Core stack: Teradata, Spark, Hive, Kafka, Airflow, Python/Scala, Terraform.
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.
What you'll do
- 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 & Optimisation: Optimise 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, containerised 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
- Education: Bachelor’s degree in Computer Science, Engineering, Information Technology, or a related discipline
- Experience: At least 10 years of data-engineering experience, with technical leadership in Teradata and Hadoop/big-data delivery.
- 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.