Senior Engineer - Data Science

Axiata Digital Labs · Bachelor's Degree · Python · SQL · ETL/ELT · 4 days ago

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Salary

≈ $16k – $40k per year (Estimated)

Location

In office (Kuala Lumpur)

Seniority

Senior · 4+ years exp

Confirmed on the employer's own hiring board on Oct 31, 2026. First seen by Alion on Oct 27, 2026. Axiata Digital Labs scores A on the Alion truth index.

Overview

Company

Impact

Profile match

Axiata Digital Labs

Axiata Digital Labs provides technology engineering for telecom operators. Its platforms cover digital channels, data and network software. The company serves operating companies across Asia.

axiatadigitallabs.com · HQ: Colombo, Sri Lanka · 1001-5000 employees · Est. 2018

Tech stack of Axiata Digital Labs

Key Responsibilities

Data Pipeline Development - Design, build, and maintain scalable data pipelines for data ingestion, transformation, and integration
Data Platform Management - Develop and optimize data infrastructure, warehouses, and processing platforms
Data Integration & Automation - Integrate data from multiple sources using APIs, streaming, and automated workflows
Data Quality & Reliability - Implement data validation, monitoring, and quality controls to ensure accurate and consistent data
Performance & Scalability - Optimize data processing, storage, and computing resources for efficiency and growth
Data Security & Governance - Implement of access controls, data protection, and governance requirements
Analytics & AI Enablement - Deliver trusted, analysis-ready datasets to support data science, AI, business intelligence, and data monetization

Person Specifications

Bachelor's degree in Computer Science, Data Engineering, Data Science, or a related field
4+ years of experience in data engineering, data platform development, or related data-focused roles
Hands-on experience in designing and maintaining scalable data pipelines, data platforms, and integration solutions
Strong proficiency in SQL, Python, and modern data engineering tools and frameworks
Experience with data warehousing, ETL/ELT processes, APIs, streaming technologies, and workflow automation
Knowledge of data quality management, monitoring, governance, and security best practices
Ability to optimize data performance and deliver trusted, analysis-ready datasets to support analytics, AI, and business intelligence initiatives

Vendor submissions - 12 months

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