About the Company
Join the centralized technology powerhouse for a leading Malaysian conglomerate. Established in early 2000s, this centre of excellence focuses on driving digital transformation, process optimization, and large-scale IT innovation across multiple business units
About the Role
We are seeking an experienced and technical Assistant Manager – Big Data & Data Solutions to manage large-scale data environments, lead technical executions, and deliver high-impact analytics solutions—particularly supporting marketing technology (MarTech) and customer analytics. In this role, you will bridge the gap between business strategy and big data engineering by designing robust data pipelines, deploying predictive models, and ensuring data quality. You will also manage and mentor junior team members to ensure the successful delivery of key data initiatives in an Agile environment.
Responsibilities
- Architecture & System Design: Design, build, and maintain enterprise big data systems aligned with stakeholder requirements and industry best practices.
- Data Engineering & Pipelines: Develop, optimize, and maintain data processing solutions using Hadoop, Spark, and Kafka to guarantee data accuracy, consistency, and integrity.
- Advanced Analytics & Machine Learning: Apply predictive modeling, clustering, regression, and NLP techniques to build customer-centric data products and uncover actionable business insights.
- Cross-Functional Collaboration: Partner with Marketing, Engineering, Product, and Strategy teams to translate complex business requirements into clear technical specifications and data architectures.
- Team Leadership & Delivery: Lead, mentor, and manage junior engineers and analysts to deliver technical tasks and projects effectively.
- Governance & Security: Ensure full compliance with data privacy, security regulations, and governance standards throughout the development lifecycle.
- Technology Modernization: Stay up to date with emerging trends in big data, AI/ML, and MarTech to introduce innovative methodologies to the organization.
Qualifications
- Big Data Technologies: Hands-on experience with big data ecosystems, specifically Spark (PySpark is a strong plus), Hadoop, or Kafka.
- Programming & Infrastructure: Strong proficiency in Python and SQL, alongside working knowledge of Terraform or Docker.
- Cloud Platforms: Experience with big data analytics platforms such as Huawei Cloud (DLI), Databricks, or Amazon EMR.
- Data Warehousing & Orchestration: Familiarity with data warehousing architectures and orchestrators like Airflow, Snowflake, BigQuery, Redshift, or Huawei DWS.
- Data Modeling & ML: Solid grasp of data modeling concepts (both supervised and unsupervised training/learning).
- Databases: Proven experience working with relational and non-relational databases, including MSSQL (preferred), PostgreSQL, and NoSQL solutions.
- Business Intelligence & MarTech: Experience with visualization tools like Power BI (preferred), Tableau, or QlikSense. Prior experience with CDP (Customer Data Platforms), MarTech tools, or the marketing industry is highly advantageous.
- Leadership & Agile: Proven ability to manage and upskill junior team members with experience working in Agile/Scrum development environments.