Principal Big Data Engineer (Contract Role)

QUESSCORP SINGAPORE PTE. LTD.; Singapore; On-site; SGD 150,000 - 190,000; Full time

Job summary

QUESSCORP SINGAPORE PTE. LTD. is seeking a senior data engineering leader to architect and operate scalable data warehouses and streaming pipelines.

You will own the end-to-end data platform, manage multi-cluster resources, and ensure secure access with audit trails. Build real-time data services with strict latency and availability targets while guiding engineers and collaborating with product teams. You will design ingestion pipelines for external sources, define data models and feature

Qualifications

• Bachelor's degree in Computer Science, Information and Computing Science, Mathematics, Statistics or related field.
• At least 8 years of professional software or data engineering experience, incl 4+ years building big data platforms.
• Hands-on production with Flink for real-time processing; Hive, HDFS and YARN experience.
• Proven experience designing multi-tenant data platforms with resource management, permissions, auditing and authentication.
• Strong Java (Spring / Spring Cloud); Python/Scala/Go knowledge is a plus.
• Strong SQL skills with MySQL, TiDB or similar databases.
• Experience building real-time data services for transactional/financial data.
• Track record of improving reliability via monitoring, fault drills and failover design.
• Solid data modelling, ETL/ELT, batch and streaming architectures knowledge.
• Ability to evaluate trade-offs and mentor engineers.

Responsibilities

• Lead architecture and development of scalable data warehouses and pipelines (Flink and Hive/HDFS).
• Own end-to-end design and operation of a big data platform with multi-cluster management.
• Build and maintain real-time data services with strict accuracy and latency targets.
• Design reliable ingestion systems for external data sources with fallbacks.
• Define data models, tagging systems and feature datasets for segmentation.
• Establish data quality, observability, monitoring and governance dashboards.
• Plan fault drills and stress tests to reduce operational risk.
• Improve processing performance, resource efficiency and platform stability.
• Provide technical guidance, conduct reviews, and mentor engineers.
• Collaborate with business/product/engineering to translate requirements into solutions.

Skills

Big data platforms

Flink real-time

Java (Spring)

SQL & distributed DBs

System reliability

Architecture decisions

Code reviews & mentoring

ETL/ELT, data modeling

Multi-tenant platforms

Python/Scala/Go knowledge

Education

Bachelor's degree in CS/related field

Tools

Hive/HDFS/YARN

Spark

Kafka

Trino

Redis

gRPC

Job description

Key Responsibilities

• Lead the architecture and development of scalable data warehouses and batch and real-time data pipelines (e.g. Flink-based streaming and Hive/HDFS-based batch processing).
• Own the end-to-end design and operation of a big data development platform, including multi-cluster resource management (e.g. YARN), access and permission controls, audit trails and unified authentication.
• Build and maintain real-time user-facing data services, such as transaction, billing and profit-and-loss analytics, with strict accuracy, latency and availability targets.
• Design reliable data ingestion and collection systems for external data sources, including primary/backup links, heartbeat monitoring, quota monitoring and fallback strategies.
• Define data models, tagging systems and feature datasets that support user segmentation, analytics and personalisation.
• Establish standards for data quality, observability, monitoring and governance, including unified monitoring dashboards and alerting.
• Plan and run fault drills and joint performance and stress tests to find bottlenecks, reduce operational risk and prepare the platform for peak-traffic events.
• Improve processing performance, resource efficiency and platform stability, and make sound scaling decisions.
• Provide technical guidance, conduct design and code reviews, and mentor engineers.
• Collaborate with business, product and engineering teams to translate requirements into dependable data solutions.

Job Requirements

Essential

• Bachelor's degree in Computer Science, Information and Computing Science, Mathematics, Statistics or a related field, or equivalent practical experience.
• At least 8 years of professional software or data engineering experience, including at least 4 years building and operating big data platforms in production.
• Hands-on experience in production with Flink for real-time processing, and with Hive, HDFS and YARN (or equivalent distributed storage, query and resource-management technologies).
• Proven experience designing and running a multi-tenant data or big data development platform, covering resource and cluster management, permissions, auditing and authentication.
• Strong proficiency in Java (including Spring / Spring Cloud microservices); working knowledge of Python, Scala or Go is an advantage.
• Strong SQL skills, including query optimisation, with experience in relational and distributed databases (e.g. MySQL, TiDB).
• Demonstrated experience building real-time data services for transactional or financial data, where accuracy and timeliness are critical.
• Track record of improving system reliability through monitoring, fault drills, failover design and performance or stress testing.
• Solid understanding of data modelling, ETL/ELT, batch and streaming architectures, and data quality practices.
• Ability to evaluate technical trade-offs, set engineering standards and mentor other engineers.

Advantageous

• Experience in payments or other regulated financial environment.
• Experience with Spark, Kafka, Trino or similar technologies.
• Experience with Redis, message queues, gRPC and distributed-systems patterns (locking, idempotency, consistency).
• Experience introducing micro-frontend or modular architectures for internal platforms.
• Experience building tagging or feature datasets for segmentation and recommendation use cases.