Description

You will build and maintain data processing pipelines for large-scale distributed systems.

This role is on-site.

Responsibilities

• Develop data processing pipelines using Python and Apache Spark (PySpark).
• Manage data flow within large-scale, distributed data systems.
• Implement ETL frameworks and data warehousing solutions.
• Utilize AWS services (S3, Glue, EMR, Redshift, Athena, Lambda) for data infrastructure.

Required Skills

• 5+ years of professional experience in data engineering.
• Strong proficiency in Python for data processing.
• Hands-on experience with Apache Spark (PySpark preferred).
• Solid experience with AWS services (S3, Glue, EMR, Redshift, Athena, Lambda).
• Expertise in SQL and relational/non-relational databases.
• Knowledge of Data Modeling and Data Warehousing concepts.
• Experience working with distributed data systems.
• Familiarity with Git and CI/CD pipelines.

Preferred Skills

• Experience with Airflow or workflow orchestration tools.
• Knowledge of Kafka, Kinesis, or streaming data platforms.

Key Skills

Education

Any Gradute