Aws Data Engineer
Posted Updated
Description
Role & Responsibilities
- Develop and maintain scalable data pipelines using AWS Glue, Amazon S3, Python, PySpark, and SQL.
- Build ETL/ELT workflows for data ingestion, transformation, and loading.
- Work with Amazon Redshift, Athena, Lambda, and other AWS services.
- Optimize data processing jobs, SQL queries, and pipeline performance.
- Implement data quality checks, validation, and error handling.
- Monitor pipeline execution, troubleshoot failures, and ensure reliable data delivery.
- Collaborate with cross-functional teams to deliver business data requirements.
Preferred Candidate Profile
- Strong hands-on experience in AWS Data Engineering.
- Proficiency in Python, PySpark, SQL, and Apache Spark.
- Experience with AWS Glue, Amazon S3, Redshift, and Athena.
- Good understanding of ETL/ELT, data warehousing, and data lake concepts.
- Knowledge of incremental data loading, partitioning, and performance tuning.
- Experience working with large datasets and production data pipelines.
- Good problem-solving, communication, and troubleshooting skills.
Perks and Benefits
- Competitive salary based on experience and skills.
- Opportunity to work on cloud-based data engineering projects.
- Learning and career growth opportunities.
- Collaborative and professional work environment.
- Exposure to modern AWS cloud technologies and data engineering tools.