Analytics Engineer: Dashboards, Datamarts & Data Modeling

CreatorIQ

Manila

On-site

PHP 1,800,000 - 2,400,000

Full time

14 days+

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Benefits offered by this job

Meal stipends
Vacation days
Wellness allowance
Parental leave
Home office stipend

Job summary

CreatorIQ is seeking an Analytics Engineer to join the GTM Ops organization in Manila. You will build high-performance Tableau dashboards and extend our dbt-based datamart layer, translating business questions into analytics that drive revenue and customer insights.

You’ll work closely with Analytics & Insights and the data engineering team to deliver self-serve analytics for GTM teams. You’ll design scalable data models, validate metrics with stakeholders, and evolve the data foundation as the

Qualifications

  • 3–5 years of analytics or BI experience.
  • Advanced Tableau skills.
  • Proficient in SQL.
  • Hands-on with dbt and dimensional modeling.
  • Proficient with Git.
  • Skilled at requirements gathering.
  • Collaborative communicator.

Responsibilities

  • Design and deliver high-impact Tableau dashboards for GTM teams.
  • Bring visualization judgment to every deliverable and select charts that fit the story.
  • Present and validate work with stakeholders, confirming analytical logic and incorporating feedback.
  • Gather and document business requirements in collaboration with GTM Strategy & Insights managers.
  • Own and extend the dimensional modeling layer, learning existing dbt models and extending datamarts.

Skills

Analytics/BI experience
Tableau
SQL
dbt modeling
Git
Requirements gathering
Collaborative communication

Job description

CreatorIQ is seeking an Analytics Engineer to join the GTM Ops organization in Manila. You will build high-performance Tableau dashboards and extend our dbt-based datamart layer, translating business questions into analytics that drive revenue and customer insights.

You’ll work closely with Analytics & Insights and the data engineering team to deliver self-serve analytics for GTM teams. You’ll design scalable data models, validate metrics with stakeholders, and evolve the data foundation as the

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