Data Engineer
This is the employer's own posting, not a copy on a job board.
What we know
Is it still open?
Confirmed still open
Last checked 2d ago — checked against the employer's own applicant tracking system, which is the company answering directly.
We re-read the employer's own applicant tracking system and the posting was still there. That is the company answering directly.
How old is it?
Posted 111d ago
The date the source published, not the day we noticed it (2026-06-22). Last seen at its source 1h ago.
We have tracked this listing since 9 Oct 2026 (2 days). The employer's own board has carried it every time we have read it, most recently 1 hour ago.
Is it remote?
LATAM (Remote)
That is the location the employer filed this posting under. Quoted as written — we do not re-word the source's own location.
Who may apply?
LATAM
The description states no restriction of its own. This is the source's own tag.
Pay not stated
Similar roles pay $3,750–7,250/mo
Middle 50% of 52 listings that do state pay — Engineering · all levels · LATAM · USD/month. This employer has published no salary; this is what comparable listings we hold disclose, never converted between currencies or periods. How this is calculated.
Skills named in the ad
Recognised terms only, from a fixed vocabulary — this is what CV matching compares against.
Carried by 1 source
-
Greenhouse employer's own board first seen 2d ago · last seen 1h ago
The listing
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.