Data Engineer
Decision Point Latam · Chile, Mexico
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
- What a data engineer actually earnsmedian, seniority, by country
- Careers a data engineer can move intoevery measured route out
- Data Architect → Data Engineer48% readiness
- Data Analyst → Data Engineer31% readiness
- All open data engineer rolesthe full board
Where these skills also reach
Adjacent occupations measured from the same postings — readiness is what a data engineer’s profile already covers.
- 36 open data architect roles92% readiness from data engineer
- 281 open data analyst roles60% readiness from data engineer
- 556 open solutions architect roles59% readiness from data engineer
- 34 open database administrator roles58% readiness from data engineer
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