Job Title: Head of Data Platform

Location: Malaysia (Hybrid/On-site)

Employment Type: Full-time

Experience Level: Senior Leadership / Head of Department

Role Overview

We are seeking an experienced Head of Data Platform (AWS & Databricks) to lead the design, implementation, and governance of enterprise-scale data platforms. This role is responsible for defining the organization’s data platform strategy, ensuring scalable and secure data architecture, and enabling data-driven decision-making across the business.

The ideal candidate will bring strong leadership capabilities, deep technical expertise in AWS cloud services and Databricks, and proven experience delivering modern data platforms that support analytics, data engineering, machine learning, and business intelligence workloads.

Key Responsibilities

Data Platform Strategy & Architecture

• Define and execute the enterprise data platform strategy aligned with organizational goals
• Lead the design of scalable, secure, and high-performance data architectures using AWS and Databricks
• Establish enterprise data standards, frameworks, and architectural principles
• Drive modernization initiatives, including migration from legacy data systems to cloud-based platforms
• Design and oversee data lake, lakehouse, and data warehouse architectures
• Ensure platform scalability to support large-scale data ingestion, processing, and analytics

Platform Engineering & Delivery

• Lead the development and deployment of enterprise data pipelines using modern data engineering frameworks
• Oversee the implementation of data integration solutions across multiple business systems
• Ensure effective use of Databricks Lakehouse architecture for analytics and machine learning workloads
• Drive automation, CI/CD pipelines, and DevOps practices for data platform delivery
• Collaborate with engineering teams to deliver reliable and efficient data workflows
• Monitor system performance and implement performance tuning strategies

AWS & Databricks Platform Management

• Oversee the configuration and management of AWS services such as:
  • Amazon S3
  • AWS Glue
  • Amazon Redshift
  • Amazon EMR
  • AWS Lambda
  • Amazon Kinesis
  • AWS IAM
• Lead adoption and governance of Databricks, including:
  • Data ingestion and transformation
  • Delta Lake implementation
  • Spark-based data processing
  • Machine learning workflows
• Manage cloud resource optimization, cost management, and scalability

Data Governance & Security

• Establish data governance frameworks, policies, and standards
• Ensure compliance with data privacy, security, and regulatory requirements
• Implement role-based access controls and data protection mechanisms
• Oversee data quality, metadata management, and data lineage frameworks
• Ensure reliable backup, disaster recovery, and data resilience strategies

Stakeholder Engagement

• Partner with business leaders to understand data requirements and priorities
• Collaborate with analytics, data science, and business intelligence teams
• Provide technical guidance to enterprise architecture and IT leadership
• Communicate platform roadmaps and progress to executive stakeholders
• Drive cross-functional collaboration across IT and business teams

Leadership & Team Management

• Lead and mentor data engineers, platform engineers, and data architects
• Build and manage high-performing data platform teams
• Define team structures, responsibilities, and performance metrics
• Support workforce planning, recruitment, and capability development
• Promote a culture of innovation, automation, and continuous improvement

Required Qualifications

• Bachelor’s Degree in Computer Science, Information Technology, Data Engineering, or related field
• 10–15+ years of experience in data engineering, data architecture, or data platform development
• 5+ years of leadership experience managing data engineering or platform teams
• Proven experience designing enterprise-scale cloud-based data platforms
• Strong expertise in:
  • AWS cloud services
  • Databricks platform
  • Distributed data processing frameworks
  • Data pipeline architecture
  • Data lake and lakehouse design
• Experience managing large datasets and high-volume data processing environments
• Strong knowledge of data architecture and platform design principles
• Excellent leadership, communication, and stakeholder management skills

Preferred Qualifications

• Experience with Databricks Lakehouse architecture
• Hands-on experience with:
  • Apache Spark
  • Delta Lake
  • Kafka or streaming technologies
  • Data orchestration tools (e.g., Airflow)
• Experience implementing real-time and batch data pipelines
• Familiarity with:
  • Machine learning platform integration
  • Data catalog and metadata management tools
  • Data visualization tools (e.g., Power BI, Tableau)
• Experience in cloud migration and data modernization initiatives
• Certifications (preferred but not mandatory):
  • AWS Certified Solutions Architect
  • AWS Certified Data Analytics
  • Databricks Certified Professional
  • Certified Data Management Professional (CDMP)

Technical Skills

• AWS Cloud Architecture
• Databricks Platform
• Apache Spark
• Delta Lake
• Data Lake & Lakehouse Architecture
• ETL / ELT Pipeline Development
• Data Integration
• Data Orchestration Tools
• CI/CD for Data Platforms
• Cloud Cost Optimization
• Data Security & Governance
• Performance Tuning & Monitoring

Functional Knowledge Areas

• Enterprise Data Architecture
• Data Engineering
• Data Governance
• Analytics Enablement
• Machine Learning Infrastructure
• Cloud Migration Strategies
• Data Quality Management
• Business Intelligence Integration

Leadership & Soft Skills

• Strategic thinking and execution
• Enterprise architecture leadership
• Stakeholder management at executive level
• Team development and mentoring
• Change management and transformation leadership
• Strong decision-making skills
• Excellent communication and presentation abilities