D

Data Engineer

Decision Point Latam · Chile, Mexico

On-siteWorkplace
1d agoPosted · Aug 17
Get on BoardSource
Apply now Opens the original posting at Decision Point Latam. PivotHop does not host applications.

Skills in this posting

Extracted from the posting text by the instrument — the demand side, read literally.

The posting

Bachelor’s degree in computer science, Engineering, Statistics, Mathematics, or related field. Master's degree preferred.

Advanced English is mandatory

1+ years of experience as Data Engineer

Cloud data storage is mandatory

Strong understanding of data modeling, ETL processes, and data warehousing concepts

Experience in SQL language, relational data modelling and sound knowledge of Database administration is mandatory

Proficiency in Python related to Data Engineering for developing data pipelines, ETL (Extract, Transform, Load) processes, and automation scripts.

Proficiency in Microsoft Excel

Experience within integrating data management into business and data analytics is mandatory

Experience working with cloud platform for deploying and managing scalable data infrastructure

Experience working with technologies such as DBT, airflow, snowflake, Databricks among others is a plus

Excellent Stakeholder Communication

Familiarity with working with numerous large data sets

Comfort in a fast-paced environment

Strong analytical skills with the ability to collect, organize, analyses, and disseminate significant amounts of information with attention to detail and accuracy

Excellent problem-solving skills

Strong interpersonal and communication skills for cross-functional teams

Proactive approach to continuous learning and skill development

Experience in leading or collaborating with a team of data scientists and engineers in developing and delivering machine learning models that work in a production setting..

Data Infrastructure Development: Design, build, and maintain scalable data infrastructure on Cloud Platforms for data processing to support various data initiatives and analytics needs within the organization

Data Pipeline Implementation: Design, develop and maintain scalable data pipelines to ingest, transform, and load data from various sources into cloud-based storage and analytics platforms using Python, and SQL

Collaboration and Support: Collaborate with cross-functional teams to understand data requirements and provide technical support for data-related initiatives and projects. Helping translating business realities into data bases solution.

Performance Optimization: Optimize data processing workflows and cloud resources for efficiency and cost-effectiveness. Implement data quality checks and monitoring to ensure the reliability and integrity of data pipelines.

Build and optimize data warehouse solutions for efficient storage and retrieval of large volumes of structured and unstructured data.

Data Governance and Security: Implement data governance policies and security controls to ensure compliance and protect sensitive information across cloud platforms environment.

Hibrido. 4x1 en Chile y 3x2 en México

2 DP Days libres por quarter

Seguro de salud complementario en Chile

almuerzo en oficina

5 días extra de vacaciones

Excerpt from the original listing. The full, current text lives at the source. Read and apply there →

The PivotHop read

Where these skills also reach

Adjacent occupations measured from the same postings — readiness is what a data engineer’s profile already covers.

More data engineer roles

Backfilled listing, refreshed with the nightly scrape; the employer has not claimed it yet. Are you the employer? Claim this listing and it can be featured to the candidates whose skills already reach it, first month free.

© 2026 PivotHopReal data, real career moves