Data Management Associate - Hybrid, Data Quality Analytics

Allegis Global Solutions; Metro Manila; Hybrid; PHP 300,000 - 420,000; Full time

Benefits offered by this job

Hybrid work setup

Midshift/nightshift schedule

Ortigas Pasig office

Job summary

Allegis Global Solutions (AGS) is seeking a Data Management Associate to support the AGS Implementation data workstream for MSP or Procurement Solutions projects. You will collect, analyze, validate, and transform incumbent worker data from multiple sources to prepare for loading into a Vendor Management System (VMS).

You will attend internal and external project calls, collaborate with vendors, clients and cross-functional teams, and help ensure data quality across multiple projects while

Qualifications

• 0-2 years of professional experience doing data analysis.
• Intermediate knowledge of MS Excel (pivot tables, VLOOKUP, formulas).
• Excellent attention to detail and data accuracy.
• Experience with data entry, analyzing information, decision making and organization.
• Strong written and verbal communication; able to multitask.

Responsibilities

• Work within a team to collect, organize and validate data using a proprietary AGS data collection tool.
• Follow up on outstanding data from outside vendors.
• Analyze data for gaps and/or errors in large data sets and resolve data issues.
• Prepare load templates for upload into Vendor Management Systems (VMS).
• Attend project meetings and communicate status of projects on weekly status calls with clients.

Skills

Data analysis

MS Excel

Attention to detail

Organizational skills

Job description

Allegis Global Solutions (AGS) is seeking a Data Management Associate to support the AGS Implementation data workstream for MSP or Procurement Solutions projects. You will collect, analyze, validate, and transform incumbent worker data from multiple sources to prepare for loading into a Vendor Management System (VMS).

You will attend internal and external project calls, collaborate with vendors, clients and cross-functional teams, and help ensure data quality across multiple projects while