Manager, Data Operations & Analytics

IMU Education; Kuala Lumpur; On-site; MYR 180,000 - 240,000; Full time

Job summary

The University seeks a Manager – Data Operations & Analytics to lead its data functions, ensuring reliable, scalable data solutions and governance across stakeholders.

You will drive ETL/ELT pipelines, data quality, and analytics delivery while guiding a data team toward continuous capability development and business impact.

Qualifications

• Bachelor’s degree in Computer Science, Data Science, IT or related field; master’s is an advantage.
• At least 10 years of overall work experience with 5+ years in lead/managerial data roles.
• Proven experience managing enterprise data platforms and large analytics projects.
• Experience with project planning, budgeting, vendor management and reporting to senior stakeholders.
• Experience contributing to data governance policies and data strategy.
• Strong leadership, mentoring and stakeholder communication skills.

Responsibilities

• Lead daily operations of data lake, data warehouse and data marts.
• Set standards for scalable ETL/ELT pipelines from multiple sources.
• Translate business requirements into technical solutions.
• Establish data quality, validation, cleansing and transformation standards.
• Oversee dashboards, reports and analytics solutions for decision-making.
• Monitor predictive and prescriptive models for performance.
• Ensure data security and governance in collaboration with ITS Cybersecurity.

Skills

SQL

Python

Cloud platforms

Data governance

ETL/ELT

Data architecture

Leadership

Stakeholder mgmt

CI/CD

JIRA

Git

Education

Bachelor's degree in CS/IT/DS

Master's degree (advantage)

Tools

AWS Glue

Athena

S3

Redshift

Spark

Hadoop

Job description

Jora Malaysia will close on 9th September 2026. Thank you for being with us, we are cheering you on as you continue your career journey.

The Manager – Data Operations & Analytics will lead the University’s data operations and analytics function, working with stakeholders across academic, corporate and ITS functions to deliver reliable, scalable and data-driven solutions aligned with institutional goals.

Key Responsibilities

Lead the daily operations of the enterprise data lake, data warehouse and data marts, ensuring reliable data ingestion, processing and monitoring.

Set the architecture, standards and best practices for scalable ETL/ELT pipelines integrating data from multiple sources.

Engage stakeholders to gather and prioritise business requirements and translate them into effective technical solutions.

Establish and enforce standards for data quality, validation, cleansing and transformation.

Guide the development and implementation of dashboards, reports and advanced analytics solutions that support strategic and operational decision-making.

Oversee the development, validation and performance monitoring of predictive and prescriptive models.

Ensure data reliability, security and compliance with internal governance requirements in collaboration with ITS Cybersecurity.

Lead cross-functional data and analytics projects, including planning, budgeting, vendor coordination and reporting to senior stakeholders.

Promote the use of machine learning, segmentation, optimisation and visualisation to generate actionable insights.

Set technical standards for coding, version control, CI/CD and reproducible development practices.

Lead, mentor and develop the data team, ensuring effective delivery and continuous capability development.

Serve as the analytics subject matter expert, advising stakeholders and leadership on the design and interpretation of reports, dashboards and analytical outputs.

Job Requirements

Bachelor’s degree in Computer Science, Data Science, Information Technology or a related field. A master’s degree is an advantage.

Minimum 10 years of overall work experience, including at least five years in a lead or managerial capacity within data engineering, analytics or data operations.

Proven experience managing enterprise data platforms, data pipelines and large-scale analytics projects.

Experience in project planning, budgeting, vendor management and reporting to senior stakeholders.

Experience contributing to data governance policies or organisational data strategy.

Strong leadership and mentoring skills, with experience developing high-performing teams.

Excellent stakeholder management and communication skills, with the ability to translate technical concepts into business value.

Strategic, organised and results-oriented, with strong analytical and problem-solving capabilities.

Proactive, adaptable and committed to continuous learning and promoting a data-driven culture.

Strong knowledge of data architecture, ETL/ELT pipelines and enterprise data platforms, including data lakes, data warehouses and data marts.

Proficiency in SQL, Python and cloud platforms such as AWS, Azure or GCP.

Experience with cloud-native data services such as AWS Glue, Athena, S3 and Redshift.

Familiarity with distributed computing technologies such as Apache Spark or Hadoop.

Experience in machine learning, advanced analytics, statistical modelling or artificial intelligence.

Ability to guide and evaluate predictive and prescriptive models, including model validation and performance monitoring.

Knowledge of data governance, metadata management, data quality, data security and privacy requirements.

Familiarity with version control, CI/CD practices and collaborative development tools such as Git and JIRA.

Ability to assess vendor solutions and integrate third-party platforms into enterprise data workflows.