Senior Data Engineer

re-zoo-me; Singapore; Hybrid; SGD 180,000 - 240,000; Full time

Job summary

re-zoo-me is seeking a senior Data Engineer to design and optimize data pipelines and lakehouse architectures in on-premise environments. You will lead end-to-end data processing, integrate with Spark/PySpark workloads, implement robust data governance, and collaborate with software, analytics, and security teams.

The ideal candidate has 8+ years in data engineering, expert SQL, strong Python, Kubernetes, Airflow, and experience with Iceberg tables, NoSQL stores, and CI/CD practices to deliver

Qualifications

• Bachelor's degree in Computer Science, IT, Engineering, or related field.
• 8+ years IT experience with 5+ years data engineering or datapipeline development.
• Expert-level SQL with SQL Server and performance tuning.
• Advanced Python for data processing and pipelines.
• Kubernetes design, deployment and management for data pipelines.
• Strong data modelling expertise (relational and non-relational).
• Experience with lakehouse/data lake architectures including Iceberg.
• CI/CD and DevOps practices, IaC and automated testing.
• ETL/ELT orchestration with Airflow or similar tools.
• NoSQL databases (MongoDB, Cassandra, etc.).
• Apache Spark / PySpark for distributed processing.
• Data security and governance including RBAC and data masking.
• Ability to work autonomously on complex projects with high code quality.

Skills

SQL Proficiency

Python

Data Modeling

Autonomy

Problem Solving

Communication

Cross-functional teamwork

Analytical skills

Education

Bachelor's degree in CS/IT/Engineering

Tools

Kubernetes

Airflow

Spark / PySpark

Iceberg

NoSQL

Git

IaC

Job description

• Bachelor's degree in Computer Science, IT, Engineering, or a related field with a demonstrated continuous learning ethos.
• Must have a minimum of 8+ years IT experience with at least 5+ years hands-on data engineering or datapipeline development
• Expert-level SQL proficiency with strong expertise in SQL Server, including queryoptimization, indexing, and performance tuning
• Advanced Python programming skills for data processing, automation, and production-grade pipeline development
• Kubernetes expertise – Design, deploy, andmanage containerized data pipelines in on-premise environments
• Strong data modellingexpertise– Both relational and non-relational concepts
• Proven experience with flexible lakehouse/data lake architecture – Multi-layer datalakes, partitioning strategies, and metadata management, Iceberg tables, and optimization
• CI/CD and DevOps practices– Setting up CI/CD pipelines, Git, automated testing, andinfrastructure-as-code tools
• ETL/ELT orchestration experience—Apache Airflow or similar tools for scheduling and monitoring batch and real-time jobs
• Hands-on experience with at least one NoSQL database (MongoDB, Cassandra, etc.)
• Hands-on experience with Apache Spark and PySpark for distributed data processing andperformance optimization
• Data security andgovernance– Role-based access control, data masking, and compliance frameworks
• Proven ability to work autonomously on complex projects while maintaining high codequality standards
• Excellent problem-solving, communication, and cross-functional collaboration skills