Requirements

Expected technologies

PySpark

AWS S3

AWS Glue

AWS EMR

AWS Lambda

AWS Redshift

Python

Azure

Google Cloud Platform

Optional technologies

SQL

Terraform

CloudFormation

Kafka

Kinesis

Our requirements

• You have hands-on experience in data engineering and can independently handle moderately complex tasks.
• You’ve worked with PySpark in distributed data processing scenarios.
• You are familiar with AWS data services such as S3, Glue, EMR, Lambda, Redshift, or similar.
• Experience working with additional major cloud platform (Azure, or GCP)
• You are proficient in Python for ETL and automation tasks.
• You communicate clearly and confidently in English.

Optional

• Strong SQL skills and understanding of data modeling.
• Exposure to CI/CD pipelines, Terraform, or CloudFormation.
• Familiarity with streaming technologies like Kafka or Kinesis.
• AWS certifications

Your responsibilities

• Design and build data pipelines using AWS services and PySpark.
• Process large-scale datasets efficiently and reliably.
• Collaborate with architects and team members to implement scalable data solutions.
• Ensure data quality, consistency, and security in cloud environments.
• Participate in code reviews and contribute to continuous improvement efforts.