freehire launches on Product Hunt on 26 August.

Follow →

Data Engineer - Latin America - Remote

Summary

Build and scale big-data infrastructure using Spark, Kafka, and Snowflake; design pipelines, warehouses, and ML platforms for AI-driven applications.

Azumo is currently looking for a highly motivated Big Data Engineer to develop and enhance data and analytics infrastructure. The position is FULLY REMOTE based in Latin America.

This position will give you the opportunity to collaborate with a growing team and bright engineering minds in big data computing. You will enjoy the role if you love designing and developing scalable, high performant big data infrastructure using Spark, Kafka, Snowflake or any similar frameworks, both on premise and in the cloud. Experience in building data pipelines, data services, data warehouses, BI and ML platforms is what we are looking for.

At Azumo we strive for excellence and strongly believe in professional and personal growth. We want each individual to be successful and pledge to help each achieve their goals while at Azumo and beyond. Challenging ourselves and learning new technologies is at the core of what we do. We believe in giving back to our community and will volunteer our time to philanthropy, open source initiatives and sharing our knowledge.

Requirements

The Data Engineer will be based remotely. Compensation commensurate with experience and candidate potential.

Basic Qualifications:

  • BS or Master’s degree in Computer Science, related degree, or equivalent experience
  • 5+ years experience with data-related and data management responsibilities
  • Deep expertise in designing and building data warehouses and big data analytics systems
  • Practical experience manipulating, analyzing and visualizing data
  • Self-driven and motivated, with a strong work ethic and a passion for problem solving
  • Professional English proficiency (B2/C1)

Preferred Qualifications:

  • Experience with cloud-based managed services like Airflow, Glue, Elastic stack, Amazon Redshift, Snowflake, BigQuery, Azure SQL Db, EMR, Azure, Databricks, Altiscale or Qubole
  • Prior experience with notebooks using Jupyter, Google Collab, or similar.

Benefits

Company benefits include:

  • Paid Time Off
  • Mentored Career Development
  • U.S. Holidays
  • USD Remuneration
  • Profit Sharing
  • Maternity Coverage
  • 100% Remote

About Azumo

Based in San Francisco, California, Azumo is an innovative software development firm specializing in AI software development services. We help companies of all sizes build intelligent applications by combining expertise in data, cloud, and AI. Our talented AI developers are trusted to deliver Top AI Development services in Generative AI, intelligent automation, and custom machine learning solutions.

At Azumo, we believe in professional and personal growth. As a recognized AI Development company, we support our engineers in mastering the latest technologies and delivering Top AI Development services worldwide. Our culture emphasizes collaboration, continuous learning, and solving complex problems with modern AI solutions. We believe in giving back to our community and will volunteer our time to philanthropy, open-source initiatives and sharing our knowledge.

If you are qualified for the opportunity and looking for a challenge please apply online at Azumo/join-our-team or connect with us at people@azumo.co

What this application asks

workable

First name, Last name, Email, Phone, Address, Resume

  • What's your current English level? choose one
  • How many years of experience do you have as a Data Engineer? choose one
  • What's your current seniority in the requested stack? choose one
  • Which Cloud provider do you have most experience with? (AWS, GCP or Azure)
  • Do you have experience with Machine Learning models? written answer
  • Do you have experience working as an international contractor? yes / no
  • Are you located in any Country in Latin America, Brazil or Caribbean? yes / no
  • What's your expected salary for this type of position? (USD/Month)

See also