Job Description

What is this position about?

- Design, build, and maintain scalable data pipelines and ingestion frameworks supporting batch processing, streaming, and change data capture (CDC) patterns.
- Develop and optimize data processing workflows using Apache Spark and PySpark, ensuring reliable and performant transformation across large datasets.
- Implement and manage data lake architectures on AWS, leveraging S3 as the primary storage layer and Apache Iceberg for table format management, schema evolution, and time-travel capabilities.
- Work with AWS-native services including Glue for ETL orchestration, Athena for serverless querying, and Lambda for event-driven data processing.
- Manage data access controls and security configurations using AWS IAM, ensuring compliant and least-privilege access across the data platform.
- Collaborate with data analysts, data scientists, and platform engineers to understand data requirements and deliver production-ready solutions.
- Monitor pipeline health, troubleshoot data quality issues, and implement improvements to ensure data reliability and freshness.
- Contribute to the documentation of data flows, architecture decisions, and engineering standards within the team.

📌 Data Engineer Analyst (Ciudad de México)
🏢 Blend360
📍 Ciudad de México