Kerja Sepenuh Masa, Analytics Engineer - MY877841 di Morgan Philips Group WP Kuala Lumpur - Maukerja

Analytics Engineer

Working Arrangement: KL (Remote)

Eligibility: Local Malaysians only (Unable to sponsor visa)

Role Overview

We are seeking a detail-oriented and proactive Analytics Engineer to join our client's high-performing data team. In this role, you will be responsible for handling end-to-end data ticket resolution, performing exploratory analytical spikes, maintaining high data accuracy, and supporting retailer-specific data models.

You will work closely with team leads in daily stand-ups to prioritize tasks, filter out data noise, and deliver accurate, business-critical outputs for our clients.

Key Responsibilities

Ticket Management & Problem Solving:

• Manage and resolve operational/support data tickets (typically around 20 tickets per week, depending on sprint volume).
• Perform end-to-end spike analysis on incoming queries and data discrepancies using SQL.
• Proactively identify data inconsistencies and implement fixes to ensure accurate, reliable data delivery.
• Group, prioritize, test, and deploy fixes efficiently within weekly sprint cycles.

Data Modeling & Analytics:

• Build and maintain tailored data models using dbt specifically for retail clients (focused on retailer-specific models rather than global architecture).
• Filter and make sense of complex dataset noise to surface actionable business insights.
• Work on analytical tasks at scale, ensuring high data fidelity on behalf of clients.

Team Collaboration & Workflow:

• Participate in daily stand-ups to align on ticket distribution, priorities, and accurate delivery timelines.
• Collaborate with the broader Data Engineering team (who handle core underlying pipeline architecture).

Requirements & Qualifications

• Advanced proficiency in SQL for data extraction, querying, and end-to-end troubleshooting.
• Hands-on experience or familiarity with dbt and Snowflake (prior experience in large enterprise or backend analytical environments is a plus).
• Strong ability to critically analyze large datasets, distinguish high-value data from noise, and accurately interpret financial/retail data patterns.
• Experience handling high-volume tickets and spike queries in an agile/sprint environment.