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 monfeichow@morganmckinley.com 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