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Data Engineer

LATAM (Remote)

Pay
Salary not listed in the saved posting
Work setup
Remote stated — work setup source
Listed location: LATAM (Remote)
Read the full posting
Employment
Unconfirmed
Apply at Nimble Gravity

What you’ll work on

Full posting
  • Build, scale, and maintain robust data solutions.

  • Collaborate closely with business stakeholders to transform use cases into production-ready services and solutions, owning the system from concept to production.

  • Implement rigorous testing and monitoring practices to maintain superior data quality and integrity.

From the employer’s posting
Primary Responsibilities Build, scale, and maintain robust data solutions. Implement and optimize high-performance data pipelines: extraction, loading, transformation, and orchestration – that are designed for scalability, reliability, maintainability, and speed.
Champion modern software engineering practices as CI/CD, infrastructure-as-code, containerization, and cloud-native deployments Collaborate closely with business stakeholders to transform use cases into production-ready services and solutions, owning the system from concept to production. Implement rigorous testing and monitoring practices to maintain superior data quality and integrity.
Collaborate closely with business stakeholders to transform use cases into production-ready services and solutions, owning the system from concept to production. Implement rigorous testing and monitoring practices to maintain superior data quality and integrity. Requirements

What you’ll bring

All qualifications

Core experience

  • 5+ years of experience in data engineering or a related discipline, with a proven track record of success.
  • Expertise in Python and SQL, with a strong foundation in data manipulation and analysis.
  • Proficient with Databricks/PySpark and dbt for data warehousing and data transformation tasks.
  • Experience with workflow orchestration tools e.g.
  • Experience working with large language models (LLMs) especially prompt engineering, retrieval-augmented generation (RAG)s, and/or vector databases are pluses.
  • Knowledge of fundamental principles of machine learning, feature engineering, and knowledge graphs are pluses.
Qualification wording
5+ years of experience in data engineering or a related discipline, with a proven track record of success.
Expertise in Python and SQL, with a strong foundation in data manipulation and analysis.
Proficient with Databricks/PySpark and dbt for data warehousing and data transformation tasks.
Experience with workflow orchestration tools e.g. Airflow, Dagster
Experience working with large language models (LLMs) especially prompt engineering, retrieval-augmented generation (RAG)s, and/or vector databases are pluses.
Knowledge of fundamental principles of machine learning, feature engineering, and knowledge graphs are pluses.

Tools in this posting

  • Python
  • SQL
  • dbt
  • Airflow
  • Databricks
  • Dagster
  • PySpark
Source — Tool mentions in context
We are looking for a Data Engineer to build and scale robust data solutions that support critical business needs. This role focuses on developing high-performance pipelines, enabling reliable data transformation, and delivering production-ready systems. The ideal candidate brings strong experience in Python, SQL, Databricks/PySpark, and modern data engineering practices. Primary Responsibilities
Competencies & Attributes - Expertise in Python and SQL, with a strong foundation in data manipulation and analysis. - Proficient with Databricks/PySpark and dbt for data warehousing and data transformation tasks.
- Expertise in Python and SQL, with a strong foundation in data manipulation and analysis. - Proficient with Databricks/PySpark and dbt for data warehousing and data transformation tasks. - Experience with workflow orchestration tools e.g. Airflow, Dagster
- Proficient with Databricks/PySpark and dbt for data warehousing and data transformation tasks. - Experience with workflow orchestration tools e.g. Airflow, Dagster - Experience working with large language models (LLMs) especially prompt engineering, retrieval-augmented generation (RAG)s, and/or vector databases are pluses.

Job description

View original posting ↗

We are looking for a Data Engineer to build and scale robust data solutions that support critical business needs. This role focuses on developing high-performance pipelines, enabling reliable data transformation, and delivering production-ready systems. The ideal candidate brings strong experience in Python, SQL, Databricks/PySpark, and modern data engineering practices.

 

Primary Responsibilities   

  • Build, scale, and maintain robust data solutions.
  • Implement and optimize high-performance data pipelines: extraction, loading, transformation, and orchestration – that are designed for scalability, reliability, maintainability, and speed.
  • Champion modern software engineering practices as CI/CD, infrastructure-as-code, containerization, and cloud-native deployments
  • Collaborate closely with business stakeholders to transform use cases into production-ready services and solutions, owning the system from concept to production.
  • Implement rigorous testing and monitoring practices to maintain superior data quality and integrity.

 

Requirements  

Education & Certificates 

  • A bachelor's degree or higher in a STEM field, required
  • Concentration in Computer Science, Math, Physics or other engineering related field, preferred 

 

Professional Experience 

  • 5+ years of experience in data engineering or a related discipline, with a proven track record of success.

 

Competencies & Attributes 

  • Expertise in Python and SQL, with a strong foundation in data manipulation and analysis.
  • Proficient with Databricks/PySpark and dbt for data warehousing and data transformation tasks.
  • Experience with workflow orchestration tools e.g. Airflow, Dagster
  • Experience working with large language models (LLMs) especially prompt engineering, retrieval-augmented generation (RAG)s, and/or vector databases are pluses.
  • Knowledge of fundamental principles of machine learning, feature engineering, and knowledge graphs are pluses.
  • Demonstrated experience in designing and implementing complex data systems from the ground up.
  • Proficient in handling large-scale data projects, including data cleaning, ETL, and information retrieval.
  • Excellent communication skills required, both verbal and written. 

 

Nimble Gravity is an Equal Opportunity Employer and considers applicants for employment without regard to race, color, religion, sex, orientation, national origin, age, disability, genetics or any other basis forbidden under federal, state, or local law. Nimble Gravity considers all qualified applicants. 

Your next step

  • Have your CV and examples of relevant work ready.
  • Check the listed location, eligibility and core experience before starting.
  • Ask the employer about the salary range before committing time to the process.

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Source & posting history

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Pay

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Location & working pattern

LATAM (Remote)

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Status in our records
Active
First seen by us
Jun 22, 2026
Recorded sightings
26
Last seen by us
Oct 7, 2026

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