Senior Data Engineer

Location: Singapore

(Priority will be given to candidates who currently possess the right to work in Singapore) About Console Connect Connecting networks, clouds and businesses, Console Connect by PCCW Global is dedicated to helping organizations overcome the barriers and complexity of connecting to the cloud. Our goal is to provide businesses with on-demand, dedicated connectivity into cloud service providers and partners around the globe, making access to business-critical applications simple, predictable and ultra-secure.

Console Connect by PCCW Global is the world's first global software-defined interconnection platform, born out of the belief that business connectivity should be simpler and more accessible for all. Console Connect enables users to efficiently manage their private connections via a user-friendly interface, regardless of their level of technical expertise. Backed by PCCW Global, one of the world's leading telecommunications groups with a tier 1 global IP network, Console Connect is completely scalable and offers maximum resilience and reliability, leaving you confident and secure in your cloud connections.

Role Overview We are passionate about harnessing the power of data to drive innovation and empower businesses. We are seeking a highly technical and experienced Senior Data Engineer to join our dynamic team. The successful candidate will be a key player in designing, building, and optimizing our data infrastructure, ensuring seamless integration and efficient data processing.

Key Responsibilities Implement and manage data workflows using tools to ensure timely and reliable execution of data pipelines Integrate data from various sources, ensuring consistency, accuracy, and reliability in the data warehouse or data lake Demonstrate strong expertise in data warehousing concepts, ETL/ELT processes, and data integration techniques Optimize existing data processes and improve efficiency and scalability. Deploy and optimize open-source solutions for data engineering tasks, leveraging their flexibility and scalability Establish engineering best practices, conduct thorough code reviews, and enhance CI/CD processes, automated testing, and code management across the team Manage and improve data infrastructure stability, monitoring, data quality automation, and lineage tracking

Minimum Qualifications Bachelor or Master Degree in relevant fields (E.g. Statistics, Computer Science, Data Science etc) 8+ years of hands-on experience in Data Engineering designing and operating large-scale data systems Strong proficiency in Python and SQL Extensive experience with modern Cloud Data Warehouses / Lakehouses (e.g., BigQuery, Snowflake, Redshift, or Databricks) Solid hands-on experience with workflow orchestration platforms (e.g., Apache Airflow, Prefect, Dagster) and data ingestion/transformation frameworks (e.g., dbt, Airbyte, Fivetran) Proficiency in Linux-based environments, containerization technologies (e.g., Docker), and Git-based collaborative workflows Deep knowledge of data warehousing architecture, data pipeline design patterns, distributed computing concepts, and performance tuning Strong problem-solving skills, independence, and the ability to collaborate effectively with cross-functional teams and stakeholders

Preferred Qualifications AI Platform Transition: Proven experience in evolving traditional data platforms toward AI-native Data Platforms AI/ML Infrastructure Ecosystem: Familiarity with vector search/indexing engines, unstructured data processing, or AI frameworks (e.g., LangChain, LlamaIndex, or agentic SDKs). Data Observability: Experience with automated data quality frameworks, data lineage tools, and advanced observability systems.