Description:

Build and maintain reliable data pipelines and ETL/ELT workflows.
Develop and optimize data models for analytics and internal tools.
Work with team members to deliver clean, trusted datasets.
Support core data platform tools like Spark and AWS (S3, SNS, SQS, ECS/Fargate, EMR).
Monitor data pipelines for quality, performance, and reliability.
Write clear documentation and contribute to test coverage and CI/CD processes.
Help shape our data lakehouse architecture and platform roadmap.

Requirements:

Bachelor's degree in Computer Science, Engineering, or a related field, or equivalent practical experience.
2–4 years of experience in data engineering or a backend data-related role.
Strong skills in Java, Scala, or another backend programming language.
Python (PySpark/pandas) skills.
Experience with SQL and distributed data systems (e.g., Spark, Kafka, SQS).
Familiarity with NoSQL stores like Cassandra, HBase, or similar.
Understanding of data modeling for analytics and reporting.
Proficient in English with strong communication skills.
Self-driven and able to learn new technologies with little guidance.
Methodical debugging skills and ability to break complex problems into smaller steps.
Open to feedback and iterative improvement through code reviews.
Uses AI-assisted engineering tools as part of daily workflow.
Reliable internet connection for video, audio, and screen sharing.

Skills

Benefits