Posted at: 16 January

Qualified Pipeline - Microstrategy Developer

Company

Data Meaning

Data Meaning is a leading Business Intelligence consulting firm headquartered in the US, specializing in Business Intelligence, Data Warehousing, and Project Management for a global B2B market.

Remote Hiring Policy:

Data Meaning is a fully remote company with team members across 13 states and 6 countries, hiring from various locations globally.

Job Type

Full-time

Allowed Applicant Locations

United States, Brazil

Job Description

Microstrategy Developer - Qualified Pipeline

Location: USA, Brazil and Latin America - 100% remote

Position type: Full-time or Part-Time

 

Position Summary

Data Meaning is a front-runner in Business Intelligence and Data Analytics consulting, renowned for our high-quality consulting services throughout the US and LATAM. Our expertise lies in delivering tailored solutions in Business Intelligence, Data Warehousing, and Project Management. We are dedicated to bringing premier services to our diverse clientele. We have a global team of 95+ consultants, all working remotely, embodying a collaborative, inclusive, and innovation-driven work culture.

Position Overview

We are proactively building a pipeline of experienced Microstrategy Developers who are passionate about data analytics and business intelligence. In this role, you will have the opportunity to work on exciting projects, leveraging your expertise in Microstrategy to drive data-driven decision-making across the organization.

Required Qualifications:

  • Minimum of 10 (ten) years of development experience with MicroStrategy 11.2 + reports, (architected as well as FF reports), dashboards, dossiers etc.
  • SQL (Structured Query Language) experience moderate to expert level
  • Excellent communication skills, comfortable speaking in groups
  • Able to work in EST or CST (US Time zones)

Preferred Qualifications:

  • Microstrategy Administration experience
  • Data Modeling
  • Data Partitioning
  • Performance Tuning
  • Understanding of common data warehousing methodology and architecture