Data Analyst with AI

ECLARO; Quezon City; On-site; PHP 480,000 - 720,000; Full time

Job summary

ECLARO is seeking a Data Analyst with AI to join our team in Manila. The role focuses on collecting, cleaning, and analyzing data to support business decisions, with emphasis on SQL, data visualization, and AI-enabled workflows.

The ideal candidate will understand insurance data structures and be comfortable working across OLTP/OLAP environments, building extraction logic and collaborating with cross-functional teams to deliver data-driven insights.

Qualifications

• 3+ years of experience in a data analyst or similar analytical role.
• Strong proficiency in SQL and experience working with relational databases.
• Understanding of OLTP vs. OLAP concepts and experience building extraction/transformation logic to populate data warehouses, data marts, or data vault models.
• Strong analytical, problem-solving, and critical-thinking skills.
• Excellent communication skills with the ability to translate technical findings for non-technical audiences.
• High attention to detail and commitment to data accuracy.

Responsibilities

• Analyze data from OLTP (transactional) systems and design/build extraction logic to feed OLAP structures such as data warehouses, data marts, and data vaults.
• Write complex SQL queries to extract and analyze data from relational databases and data warehouses.
• Familiarity with the insurance domain — Policy, Claims & Billing.
• Strong technical skillset, with the willingness and ability to take on tasks outside core competency as needed.
• Gather, clean, and validate data from multiple internal and external sources, including core insurance systems.
• Perform data analysis to identify trends, patterns, and insights that guide business strategy and decision-making.
• Collaborate with cross-functional teams to support data-driven projects and initiatives.

Skills

SQL

Data Visualization

AI/ML Concepts

Analytical Thinking

Communication

Tools

Guidewire

Job description

Data Analyst with AI

We are seeking a detail-oriented and analytical Data Analyst with AI knowledge to join our team. This role will be responsible for collecting, cleaning, analyzing, and interpreting data to support business decision-making.

The ideal candidate must have strong SQL and data visualization skills; should be able to leverage AI to build skills to perform tasks efficiently, a solid understanding of insurance or policy administration data structures, and preferably knowledge of Guidewire and Guidewire Data model.

Key Responsibilities:

• Analyze data from OLTP (transactional) systems and design/build extraction logic to feed OLAP structures such as data warehouses, data marts, and data vaults.
• Write complex SQL queries to extract and analyze data from relational databases and data warehouses.
• Familiarity with the insurance domain — Policy, Claims & Billing.
• Strong technical skillset, with the willingness and ability to take on tasks outside core competency as needed.
• Gather, clean, and validate data from multiple internal and external sources, including core insurance systems.
• Perform data analysis to identify trends, patterns, and insights that guide business strategy and decision-making.
• Collaborate with cross-functional teams to support data-driven projects and initiatives.

Required Qualifications:

• 3+ years of experience in a data analyst or similar analytical role.
• Strong proficiency in SQL and experience working with relational databases.
• Understanding of OLTP vs. OLAP concepts and experience building extraction/transformation logic to populate data warehouses, data marts, or data vault models.
• Strong analytical, problem-solving, and critical-thinking skills.
• Excellent communication skills with the ability to translate technical findings for non-technical audiences.
• High attention to detail and commitment to data accuracy.

Preferred Qualifications:

• Experience working with Guidewire or other P&C insurance systems.
• Exposure to AI agents, including building agents to drive efficient outcomes.