Data Analysis, Lead

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About the Role

Reporting line: Senior Manager, Data Analysis & Data Science
Location: Hochiminh City
Function: Customer & Information Technology | Department: Enterprise Data
Role: Individual Contributor

The Opportunity:

We are looking for Data Analysis, Lead who is responsible for
- Analyze and interpret complex data sets (both structured and unstructured), identify patterns and trends by applying analytical methods, techniques, model, and collaborate with business stakeholders to translate data findings into actionable strategies and actions.
- Provide critical insights through reports, visualization, and storytelling with the objective of improving business decision-making and strategy, all within established data governance policies and available resources.
- Use and manage data analytics infrastructure such as data warehouses and data marts, and Self-Service BI systems such that analytics can be provided with greater precision and in a timely manner.

Roles and Responsibilities:

A. Data Analysis & Insights

- Identify trends and patterns in large datasets.

- Provide actionable insights to support strategic and operational business decisions.

- Conduct ad-hoc and deep-dive analyses for various business units.

B. Data Systems & Integrity

- Maintain and manage data collection systems and databases.

- Ensure data integrity, accuracy, and availability.

- Collaborate with data governance teams to uphold data quality, lineage, and security protocols.

C. Data Visualization & Reporting

- Develop interactive dashboards and reports for stakeholders.

- Communicate findings and recommendations clearly to technical and non-technical audiences.

- Use visualization tools to support strategic planning and performance tracking.

D. Experimentation & Advanced Analytics

- Design and analyze experiments to validate business hypotheses.

- Interpret results to guide product development and strategic initiatives.

- Build models and perform advanced analytics to uncover hidden insights.

E. Cross-Functional Partnership

- Partner with business leaders to define KPIs and success metrics.

- Serve as a strategic advisor to teams in marketing, finance, operations, and product.

- Support business teams with data modeling and advanced analytics.

F. Data Engineering & Automation

- Collaborate with data engineers to implement CI/CD pipelines for analytics assets.

- Work with analytics engineers and data scientists to design robust data models and pipelines.

- Ensure reproducibility, scalability, and collaboration across analytics projects.

G. Enablement & Mentorship

- Mentor business users in self-service analytics tools and data literacy.

- Promote a data-driven culture across the organization.

Requirements:

- Bachelor's degree in computer science, Information Technology, Information Systems or in any field with an emphasis on computing and IT with quantitative techniques.

- At least 5 years of experience in, data analysis, data engineering, data science or a related field such as software engineering.

Relevant certifications such as Microsoft Certified: PowerBI Data Analysts Associate, Databricks certified Data Engineering Associate, Microsoft Certified Fabric Analytics Engineer. Microsoft Fabric Data Engineer

Technical Skills:

• Data Analysis: Proficiency in analyzing large complex data sets using statistical methods and tools.
• Data Engineering: Experience with ETL/ELT processes to move and transform data, Ability to develop, construct, test, and maintain data pipelines.
• Cloud Platforms: Experience with cloud services specifically Azure for scalable data solutions and Databricks analytics platform.
• Tools and Software: proficiency in tools such as SQL, Python, Power BI
• Database Management and Data Modelling: Proficiency in data modelling, schema design applying industry standard methodologies to structure enterprise-wide warehouses and subject area-marts which provide consistency, availability and scalability.
• Business Acumen: Ability to translate business requirements into data analysis tasks and provide insights that drive strategic decisions.
• Data management: Experience in implementing meta-data management tools, exposure to Azure purview / data bricks unity catalog for lineage and data discovery and enhancing governance and transparency.
• Data Ops: Experience with Git, experience in code deployment workflows for BI tools and data transformation scripts. Experience in Monitoring data pipeline performance and implementing alerting systems for analytical workloads.

- Soft Skills: The company seeks a proactive, detail-oriented individual who is curious and passionate about data. They should be a team player with strong interpersonal skills.

• Analytical Thinking: Strong problem-solving skills and the ability to think critically about data.
• Communication: Excellent verbal and written communication skills to effectively present findings and insights.
• Attention to Detail: High level of accuracy and attention to detail in data analysis and reporting.
• Collaboration: Ability to work well with cross-functional teams and stakeholders.
• Adaptability: Flexibility to adapt to changing business needs and priorities.