Aws data ecosystem (glue, s3, athena, managed airflow, iceberg)
Design, implement, and evolve a petabyte-scale AWS data platform, applying advanced engineering, distributed systems principles, and cloud-native practices to ensure performance, reliability, and scalability
Job Summary
Design, implement, and evolve a petabyte-scale AWS data platform, applying advanced engineering, distributed systems principles, and cloud-native practices to ensure performance, reliability, and scalability.
Build and optimize highly scalable data pipelines using Scala, Spark, and cloud-native services, ensuring efficient, resilient, and production-ready data processing that supports analytics and downstream products.
Act as a principal-level technical leader, mentoring engineers, driving high-quality code reviews, and promoting best practices to elevate engineering maturity across the organization.
Matching Summary
Design, implement, and evolve a petabyte-scale AWS data platform, applying advanced engineering, distributed systems principles, and cloud-native practices to ensure performance, reliability, and scalability.
Skills & Requirements
Must-have
Petabyte-scale AWS data platform
Scala and Apache Spark
AWS data ecosystem (Glue, S3, Athena, Managed Airflow, Iceberg)
Distributed systems and parallel workloads
Query optimization and data partitioning
Agile environments
Nice-to-have
DBT or modern transformation frameworks
Concurrent and parallel programming
Vector databases
AI/LLM techniques
Key Requirements
Expert-level software and data engineering experience
Bachelor’s degree in Computer Science, Engineering, or equivalent experience