Senior Data Engineer

Company Summary A leading telecommunications company has launched a new business unit dedicated to Artificial Intelligence & Data Analytics — a strategic engine driving enterprise-wide AI transformation. This unit is tasked with embedding intelligence into every layer of the business, aligning people, platforms, and processes to build AI literacy and create a culture where intelligence augments human potential. Joining this team means contributing to a company-wide shift reshaping the telecom industry through AI-driven innovation. Roles & Responsibilities

• Design, build, and operate scalable batch and streaming data pipelines (using tools like Databricks and Kafka) across a hybrid cloud data platform, ensuring reliability, security, and alignment with enterprise architecture standards.

• Perform data transformation and cleansing (PySpark/SQL) to meet business and technical requirements.

• Monitor, troubleshoot, and ensure the quality and reliability of data workflows.

• Lead integration of data from diverse sources (files, APIs, databases, streaming platforms), coordinating with source-system owners and consuming teams.

• Lead the implementation of knowledge base and Retrieval-Augmented Generation (RAG) solutions to support scalable GenAI and agentic AI use cases, including storage, lifecycle management, and embedding/vectorization.

• Provide technical guidance to engineers and delivery partners on platform patterns, code quality, and production support practices.

• Own production readiness for assigned components — observability, incident triage, root-cause analysis, and operational runbook improvements.

• Maintain metadata/pipeline documentation and contribute to CI/CD automation efforts.

• Apply data governance, security, and access control policies throughout solution design and implementation.

Requirements

• Bachelor's degree in Computer Science, Engineering, or related field.

• 5–8 years of experience in data engineering, data platform engineering, or cloud-scale analytics delivery, with proven ownership of production pipelines.

• Hands-on expertise in Python, SQL, and Apache Spark (PySpark) for large-scale data processing.

• Experience building knowledge base/RAG solutions for agentic AI use cases.

• Strong understanding of enterprise data architecture, cloud security, CI/CD, release management, and production operations.

• Self-starter with strong problem-solving skills, attention to detail, and the ability to lead technical discussions across engineering, architecture, and business stakeholder groups.

• Strong documentation and communication skills.

If you're interested in the above role, click on the 'apply' function now! Alternatively, you can contact Mon Fei at [email protected] for a confidential discussion. Only shortlisted candidates will be notified. Morgan McKinley Pte Ltd Chow Mon Fei EA Licence No: 11C5502 EA Registration No. R1877534