Description

The ideal candidate has 4–10+ years of experience in data engineering and deep hands-on expertise with Apache Iceberg, especially around table design, schema evolution, and performance optimization. Strong experience with AWS data services, Python, distributed processing frameworks like Spark or Flink, and building scalable ETL/ELT pipelines is required. Solid SQL and data modeling skills are essential, while experience with Kafka is a plus. The role also includes collaborating with cross-functional teams, contributing to system design and architecture discussions, and helping establish best practices for data governance, monitoring, and reliability.

Must Have:

• Experience building and deploying a data warehouse/lake 
• Deep experience with AWS data stack: S3, EMR, Lambda, Glue, IAM, Step Functions, CloudWatch
• Fluency in Python for data pipelines, automation, and APIs.
• Experience with distributed engines such as Spark, Flink, or PySpark.
• Expertise in scalable ETL/ELT pipelines and real-time streaming architectures.
• Strong SQL and data modeling expertise

Key Skills

Education

Bachelor's degree