Analytics Engineer

Job Summary

The Analytics Engineer is responsible for collecting, preparing, and analyzing data to support decision making across the organization. This role focuses on ensuring data accuracy and integrity, developing reports and dashboards, and providing actionable insights to business teams. The Analytics Engineer collaborates with cross-functional units to address data needs, perform statistical analyses, and contribute to the continuous improvement of data processes and governance.

Position Requirements

Education

• Bachelor’s degree in Statistics, Mathematics, Economics, Computer Science, or a related quantitative field.

Experience

• Prior experience or internship in data analysis, data engineering, or business intelligence roles.
• Familiarity with SQL and database concepts.
• Exposure to data visualization tools (e.g., Tableau, Power BI, Superset).

Skills and Competencies

• Strong analytical and problem-solving skills.
• Basic programming knowledge in Python or R (preferred).
• Excellent written and verbal communication skills.
• Strong attention to detail and commitment to data accuracy.
• Ability to work independently and as part of a collaborative team.
• Eagerness to learn and adapt to new technologies.

Preferred Qualifications

• Knowledge of data warehousing concepts (e.g., Snowflake, BigQuery, Redshift).
• Experience in industries such as e-commerce, marketing, or finance is a plus.

Job Responsibilities

Data Collection and Preparation

• Gather data from multiple primary and secondary sources, ensuring accuracy and completeness.
• Perform data cleaning, transformation, and validation to prepare datasets for analysis.
• Assist in the development and maintenance of databases and data systems.

Data Analysis and Interpretation

• Conduct statistical analysis and data mining to identify trends, patterns, and correlations.
• Support the development of analysis methodologies and techniques.
• Interpret data and analyze results using statistical and analytical approaches.

Reporting and Visualization

• Create and maintain regular and ad-hoc reports, dashboards, and visualizations.
• Present data clearly and effectively using charts, graphs, and tables.
• Ensure accuracy, clarity, and timeliness of reports delivered to stakeholders.

Collaboration and Communication

• Work with Marketing, Sales, Operations, and other teams to understand data needs.
• Provide analytical support and communicate findings to technical and nontechnical audiences.
• Actively participate in team meetings and contribute to discussions on data use.

Data Quality and Governance

• Identify and resolve data discrepancies to maintain quality and integrity.
• Follow established data governance policies and procedures.
• Document data sources, methodologies, and processes for transparency and consistency.

Professional Development

• Stay up to date with industry trends, tools, and best practices in analytics.
• Continuously improve skills in data analysis tools and programming languages.
• Participate in training and development initiatives.

Picture of Success

An effective Analytics Engineer will be considered successful when:

• Accurate, reliable, and timely reports and dashboards are consistently delivered to stakeholders.
• Data is cleaned, validated, and maintained to support high-quality analysis.
• Insights generated from analysis are used to inform marketing, sales, finance, and operations

strategies.

• Collaboration with cross-functional teams leads to stronger data-driven decision making.
• Continuous improvements are made to data quality, documentation, and governance practices.

Job Types: Full-time, Fixed term
Contract length: 24 months

Benefits:

• Health insurance
• Life insurance

Application Question(s):

• How much is your expected salary? (Do not leave blank)
• Are you willing to work in a Hybrid setup in Makati/Mandaluyong (3 days RTO per week)?

Work Location: Hybrid remote in Mandaluyong