AWS Data Engineer
Worldwide | Sept. 17, 2026
Report as Closed
Company:
DSAC Chile
Country: Worldwide
Type: Remote
Employment: Full-time
Description: DSAC is a Chilean technology company specialized in the development of technological solutions, artificial intelligence, cybersecurity and automation for companies seeking to improve their efficiency and generate real impact on their business.
None
Training:
- Professional degree in Engineering (Computer Science, Civil, or similar)
Experience:
- 4 to 5 years in data engineering roles
- Experience in cloud solutions, ideally AWS
🧠 Technical knowledge (exclusive)
- AWS: S3, Glue, Lambda, Redshift, Athena, Step Functions, IAM, CloudWatch
- Python and advanced SQL
- ETL/ELT processes
- Data modeling (Data Warehouse, Data Lake, Lakehouse)
- Relational and analytical databases
- Git and good development practices.
💡 Key competencies
- Thinking analytical and problem solving
- Effective technical communication
- Adaptability and agile work
- Collaboration and teamwork
- Attention to detail
At DSAC Chile, recognized among the Top 10 Happiest Companies in Chile, we are looking for our next Data Engineer - AWS to join a team that transforms the future with technology, innovation and excellence.
More than technical knowledge, we value people who share our culture of collaboration, customer orientation and constant search for excellence. Each selection process is an opportunity to grow together and build the future of technology.
🚀 What will be your impact? Design, develop, implement and optimize data engineering solutions in AWS environments, ensuring the correct ingestion, transformation, storage, quality and availability of corporate information, with the aim of enabling analytical processes, advanced reporting, data governance and decision making based on reliable data for the different areas of the business.
Main Responsibilities:
- Design and build data pipelines (ETL/ELT) in AWS
- Implement data ingestion, transformation and storage processes
- Model data for analytical environments (Data Lake / Data Warehouse / Lakehouse)
- Automate and orchestrate data flows
- Ensure quality, traceability and data governance
- Optimize performance and costs in cloud environments
- Collaborate with BI, analytics, architecture and business teams
- Monitor processes and propose continuous improvements
➕Desirable
- PySpark, EMR, Kinesis, EventBridge, Airflow
- CI/CD, DataOps or DevOps
- Terraform or infrastructure as code
- Governance and data quality
- AWS Certifications
- Experience in high-volume industries (retail, e-commerce, financial, etc.)
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