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GEOHidráulica Tech Stack

Submersible and stationary pump manufacturer and rental operator in Peru

Mechanical Or Industrial Engineering La Molina, Lima 201–500 employees Founded 2007 Privately Held

GEOHidráulica manufactures and rents submersible and stationary pumps for mining and industrial operations across Peru. The tech stack—SQL, Python, R, Power BI, Tableau, Looker Studio—combined with active projects around data orchestration and automated reporting, suggests the company is scaling internal analytics to replace manual processes and reduce data latency across operations and maintenance workflows.

Tech Stack 10 technologies

Core StackPower BI Tableau Python Power Query Microsoft Office Looker Studio SQL R DAX FANUC

What GEOHidráulica Is Building

◆Challenges

Eliminating manual reporting processes
Reducing data response times

▲Active Projects

Data flow orchestration and dashboard creation
Automating reporting processes
Continuous data architecture improvement

Hiring Activity

Accelerating15 roles · 9 in 30d

Department

Manufacturing

7

Engineering

3

Logistics

2

Data

1

Finance

1

Ops

1

Seniority

Mid

7

Junior

6

Intern

1

Senior

1

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About GEOHidráulica

GEOHidráulica is a Peruvian pump systems company founded in 2007, operating across manufacturing, rental, repair, and technical services. The company specializes in its proprietary HIDROpump submersible pump line, along with rental inventory of both submersible and stationary units. Core services include pump maintenance, system operation support, and technical consulting for mining and industrial customers. The workforce spans manufacturing, engineering, logistics, and emerging data functions, with hiring accelerating across mid-level technical roles.

HeadquartersLa Molina, Lima

Company Size201–500 employees

Founded2007

Hiring MarketsPeru

Frequently Asked Questions

What technology does GEOHidráulica use for analytics and reporting?

GEOHidráulica uses Power BI, Tableau, and Looker Studio for dashboarding, with SQL, Python, and R for data processing. The stack is applied to automate reporting and improve data architecture.