Senior Data Engineer

Trinity Consulting Services; Singapore; On-site; SGD 120,000 - 180,000; Full time

Job summary

Trinity Consulting Services is seeking an senior data engineer to design and implement robust data pipelines and lakehouse architectures in on-prem environments.

You will work across data ingestion, modeling, and governance, using Spark, PySpark, Airflow, and Kubernetes, with a strong emphasis on performance and secure data handling.

Qualifications

• Bachelor's degree in CS/IT/Engineering or related field with ongoing learning
• 8+ years IT experience with 5+ years data engineering/ datapipeline development
• Expert-level SQL proficiency incl. SQL Server performance tuning
• Advanced Python for data processing and production-grade pipelines
• Kubernetes design, deployment of containerized pipelines on premise
• Strong data modelling for relational and non-relational systems
• Experience with lakehouse architectures, Iceberg, partitioning, metadata
• CI/CD, DevOps practices, IaC, Git, automated tests
• ETL/ELT orchestration with Apache Airflow or similar
• NoSQL databases (MongoDB, Cassandra) hands-on
• Apache Spark / PySpark for distributed processing
• Data security and governance, RBAC, data masking
• Autonomous work on complex projects with high code quality
• Excellent problem-solving and cross-functional collaboration

Responsibilities

• Design, build and optimize data pipelines and data lakes.
• Collaborate with data science and analytics teams to deliver reliable datasets.
• Implement data governance and security controls across environments.
• Develop and maintain scalable ETL/ELT workflows with Airflow.
• Tune SQL queries and data models for performance and scalability.
• Mentor teammates and promote best practices in coding and testing.

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