Data Engineer
Hybrid · Santiago, Santiago Metropolitan, Chile
Job Summary
Data Engineer (Senior) to design, build, and optimize scalable cloud-based ETL/ELT pipelines in AWS. Lead data ingestion, transformation, and enrichment workflows, implement CDC patterns, and support multiple data domains. Mentor junior and mid-level engineers, contribute to architecture discussions, code reviews, and technical planning. Leverage AI-assisted development tools and best practices to deliver reliable, scalable data solutions within an AWS-based ecosystem. Strong experience with Python, PySpark, and AWS data services is required. Hybrid work arrangement available in Santiago, Chile.
Required Qualifications
- Strong experience in Data Engineering
- Strong expertise with AWS services (AWS Glue, Amazon S3, Amazon Athena, AWS Step Functions)
- Advanced proficiency in Python and PySpark
- Experience designing scalable data pipeline architectures
- Hands-on experience implementing CDC patterns
- Solid understanding of data modeling and large-scale data processing
- Experience leading technical initiatives and mentoring engineering teams
- Experience working within Agile environments
- Familiarity with AI-assisted development workflows and engineering productivity tools
- Excellent written and verbal English communication
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