Job Description:

Key Skills:

AWS, SQL, AWS Cloud, Pyspark, Databricks, Python, Redshift, Hadoop

Roles and Responsibilities:

- Develop and maintain ETL/ELT pipelines using Python and PySpark for large-scale data processing.

- Write and optimize SQL for data modeling, transformations, and analytics workloads.

- Build and orchestrate data jobs using AWS Glue and AWS Databricks, ensuring efficient execution and maintainable code.

- Design data ingestion and transformation workflows that load curated datasets into Amazon Redshift.

- Monitor pipeline performance, troubleshoot data issues, and improve reliability and processing efficiency.

Skills Required :

- 5-10 years of relevant experience in data engineering

- Python (including common resume forms like py or python)

- PySpark for distributed data processing and transformations

- SQL for querying, data modeling, and performance optimization

- AWS Glue, AWS Databricks, and Amazon Redshift for building production data pipelines and analytics storage

Education :

- Bachelor's Degree in Computer Science or related field