Data Team Lead

Hua Ao; Kuala Lumpur; On-site; MYR 180,000 - 300,000; Full time

Job summary

Hua Ao in Kuala Lumpur, Malaysia, is seeking a Data Team Lead to steer the design, development and governance of scalable data platforms, enabling business growth through analytics, automation and AI.

You will lead data engineering, BI, reporting and AI initiatives, collaborate with Product, Engineering, Operations, Risk, Finance and Compliance to build reliable data solutions, improve efficiency and support strategic decisions.

Qualifications

• Bachelor's degree in Computer Science, Data Science, Information Systems, Statistics or a related field.
• 6-8+ years of experience in Data Engineering, Analytics or Business Intelligence.
• 2-3 years of people management experience leading technical teams.
• Strong experience in SQL and Python.
• Experience with modern data warehouses such as Snowflake, BigQuery, Redshift or Databricks.
• Experience building ETL/ELT pipelines and data integration solutions.
• Strong understanding of data modelling, database design and data governance.
• Experience with BI platforms such as Power BI, Tableau or Looker.
• Experience working in cloud environments (AWS, Azure or GCP).
• Excellent analytical, communication and stakeholder management skills.

Responsibilities

• Lead, mentor and develop a data team of engineers and analysts.
• Define team objectives, KPIs and development plans.
• Oversee workload planning, project prioritization and resource allocation.
• Foster a data-driven culture across the organization.
• Design, build and maintain scalable data pipelines, ETL/ELT processes and data warehouses.
• Ensure high standards of data quality, integrity, availability and security.
• Develop scalable data architecture to support business growth and increasing transaction volumes.
• Optimize data processing performance and system reliability.
• Deliver actionable dashboards, reports and self-service analytics using BI tools.
• Partner with business stakeholders to define KPIs and reporting requirements.
• Perform exploratory data analysis to identify trends, risks and business opportunities.
• Translate complex data into meaningful business insights.
• Identify and implement AI solutions to improve operational efficiency and business decision-making.
• Develop AI-enabled reporting, forecasting and anomaly detection capabilities.
• Evaluate and deploy Generative AI tools to enhance productivity.
• Collaborate with engineering teams to integrate AI models into operational workflows.
• Drive intelligent process automation using ML, LLMs and AI analytics.
• Promote responsible AI practices, including governance, security and data privacy.
• Establish data governance frameworks, data standards and ownership.
• Ensure compliance with internal policies, regulatory requirements and data protection standards.
• Support audit requests and regulatory reporting where applicable.
• Maintain proper documentation for data assets and processes.
• Work closely with Product, Engineering, Risk, Finance, Operations and Compliance teams.
• Support strategic initiatives through data modelling and analytical insights.
• Lead cross-functional data projects from planning through implementation.
• Communicate technical concepts effectively to non-technical stakeholders.
• Drive continuous improvement of data platforms, reporting processes and analytics capabilities.
• Evaluate emerging technologies in AI, cloud data platforms and modern analytics.
• Recommend best practices for data engineering, governance and AI adoption.
• Build a scalable roadmap for future data capabilities.

Skills

SQL

Python

People management

Data analysis

Data modelling

Education

Bachelor's degree in Computer Science, Data Science, Information Systems, Statistics or related field

Tools

Snowflake

BigQuery

Redshift

Databricks

Power BI

Tableau

Looker

Job description

The Data Team Lead is responsible for leading the company's data function, driving the design, development and governance of scalable data platforms while enabling business growth through data analytics, automation and Artificial Intelligence (AI).

This role combines technical leadership with people management, overseeing data engineering, business intelligence, reporting and AI initiatives. The successful candidate will work closely with Product, Engineering, Operations, Risk, Finance and Compliance teams to build reliable data solutions, improve operational efficiency and support strategic decision-making.

Key Responsibilities

• Lead, mentor and develop a high-performing data team, including Data Engineers, BI Analysts and Data Analysts.
• Define team objectives, KPIs and development plans aligned with business priorities.
• Manage workload planning, project prioritization and resource allocation.
• Foster a data-driven culture across the organization.
• Design, build and maintain scalable data pipelines, ETL/ELT processes and data warehouses.
• Ensure high standards of data quality, integrity, availability and security.
• Develop scalable data architecture to support business growth and increasing transaction volumes.
• Optimize data processing performance and system reliability.

Business Intelligence & Analytics

• Deliver actionable dashboards, reports and self-service analytics using BI tools.
• Partner with business stakeholders to define KPIs and reporting requirements.
• Perform exploratory data analysis to identify trends, risks and business opportunities.
• Translate complex data into meaningful business insights.

AI & Automation

• Identify and implement AI solutions to improve operational efficiency and business decision-making.
• Develop AI-enabled reporting, forecasting and anomaly detection capabilities.
• Evaluate and deploy Generative AI tools to enhance productivity across business functions.
• Collaborate with engineering teams to integrate AI models into operational workflows.
• Drive intelligent process automation using machine learning, LLMs and AI-assisted analytics where appropriate.
• Promote responsible AI practices, including governance, security and data privacy.

Data Governance & Compliance

• Establish data governance frameworks, data standards and ownership.
• Ensure compliance with internal policies, regulatory requirements and data protection standards.
• Support audit requests and regulatory reporting where applicable.
• Maintain proper documentation for data assets and processes.

Cross-functional Collaboration

• Work closely with Product, Engineering, Risk, Finance, Operations and Compliance teams.
• Support strategic initiatives through data modelling and analytical insights.
• Lead cross-functional data projects from planning through implementation.
• Communicate technical concepts effectively to non-technical stakeholders.
• Drive continuous improvement of data platforms, reporting processes and analytics capabilities.
• Evaluate emerging technologies in AI, cloud data platforms and modern analytics.
• Recommend best practices for data engineering, governance and AI adoption.
• Build a scalable roadmap for future data capabilities.

Qualifications

• Bachelor's degree in Computer Science, Data Science, Information Systems, Statistics or a related field.
• 6-8+ years of experience in Data Engineering, Analytics or Business Intelligence.
• At least 2-3 years of people management experience leading technical teams.
• Strong experience in SQL and Python.
• Experience with modern data warehouses such as Snowflake, BigQuery, Redshift or Databricks.
• Experience building ETL/ELT pipelines and data integration solutions.
• Strong understanding of data modelling, database design and data governance.
• Experience with BI platforms such as Power BI, Tableau or Looker.
• Experience working in cloud environments (AWS, Azure or GCP).
• Excellent analytical, communication and stakeholder management skills.

Preferred Qualifications

• Experience in FinTech, Payments, Banking or Financial Services.
• Experience with payment transaction data, settlement or reconciliation systems.
• Hands-on experience with AI technologies, including:
• Prompt Engineering
• AI Agents
• Retrieval-Augmented Generation (RAG)
• Machine Learning applications
• Experience integrating OpenAI, Azure OpenAI, Anthropic, Gemini or similar AI platforms.
• Familiarity with vector databases, embeddings and semantic search.
• Experience leading AI transformation or enterprise AI adoption initiatives.
• Knowledge of MLOps and AI governance frameworks.