AWS Data Engineer (Standard)

• Experience: 4-6 years of professional technology experience
• Data Ingestion:
• 4+ years of experience in developing data ingestion pipelines using PySpark (both batch and streaming)
• Proficient in AWS data engineering services, such as Glue, Athena, DynamoDB, Kinesis, Kafka, Lambda, Redshift
• Redshift Expertise:
• 1+ years working with Redshift (loading data from S3/on-prem sources into Redshift)
• Optimizing data ingestion into Redshift
• Designing, developing, and optimizing queries on Redshift using SQL or PySparkSQL
• Table design experience (e.g., distribution key, compression, vacuuming, etc.)
• API Development: Experience in developing applications that consume services exposed as ReST APIs
• SQL Skills: Ability to write and analyze complex and performant SQL queries
• ETL Pipeline Development:
• 2+ years of experience developing and supporting ETL pipelines using enterprise-grade tools like Pentaho, Informatica, Talend
• Data Modeling: Knowledge of data modeling, design patterns, and best practices
• Reporting Technologies: Experience with Reporting tools like Tableau or PowerBI

Key Skills:

• PySpark for data pipeline development
• Advanced SQL for data extraction, analysis, and reporting
• Experience with data ingestion and platform configuration migration
• Strong debugging and problem-solving skills
• Collaboration with Data Architects and innovation-driven contributions