Data Engineer at TIDAL
Lima, Lima, Peru -
Full Time


Start Date

Immediate

Expiry Date

08 May, 25

Salary

3000.0

Posted On

09 Feb, 25

Experience

3 year(s) or above

Remote Job

No

Telecommute

No

Sponsor Visa

No

Skills

Analytical Skills, Latin America, Ansi X12, Data Flow, Data Integrity, Edifact, Data Processing, Communication Skills, Data Engineering, English

Industry

Information Technology/IT

Description

QUALIFICATIONS:

  • Must be based in Latin America.
  • At least 3-5 years of freelancing experience.
  • 3+ years of professional experience in data engineering, EDI development, or system integrations.
  • Proven experience working with e-commerce platforms and ERP systems.
  • Strong proficiency in EDI formats (e.g., ANSI X12, EDIFACT) and integration protocols (e.g., AS2, SFTP, API).
  • Excellent problem-solving and troubleshooting skills for data flow and integration challenges.
  • Familiarity with cloud-based infrastructure and tools for data processing.
  • Strong analytical skills and attention to detail to ensure data integrity.
  • Ability to work independently, prioritize tasks, and meet deadlines in a fast-paced environment.
  • Excellent communication skills in English (Spanish or Portuguese fluency is a plus).
Responsibilities

ABOUT THIS ROLE:

As a Data Engineer (EDI/Integrations), you will design, build, and maintain efficient data integration pipelines and processes to support our clients’ e-commerce operations. You will be instrumental in streamlining Electronic Data Interchange (EDI) systems, ensuring seamless communication between partners, vendors, and internal systems. This role requires expertise in data engineering, integration tools, and an ability to translate business needs into scalable technical solutions.

KEY RESPONSIBILITIES:

  • Develop, implement, and manage EDI workflows, ensuring accurate and timely data exchanges between systems and partners.
  • Design and maintain data pipelines to support integrations between e-commerce platforms, ERPs, and other business systems.
  • Collaborate with cross-functional teams to gather and define data requirements for integrations and reporting.
  • Monitor and troubleshoot data flow issues, providing timely resolutions to minimize disruptions.
  • Optimize data processing and integration performance to ensure scalability and efficiency.
  • Ensure data accuracy, integrity, and security across all integration processes.
  • Create detailed documentation for integration processes, data flow diagrams, and system architectures.
  • Stay updated on data engineering trends, tools, and best practices to recommend innovative solutions.
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