AWS Data Engineer

Primary Responsibilities:

• Proven hands-on experience in AWS Data Engineering within extensive cloud data environments
• Proficient in AWS services including S3, Glue, Lambda, Redshift, Lake Formation, CloudWatch, and IAM
• Extensive background in real-time and streaming data processing utilizing Amazon Kinesis Data Streams, Kinesis Firehose, Kinesis Analytics, Amazon Kafka, or similar streaming solutions
• Demonstrated coding expertise in Python, PySpark, and SQL, with a focus on optimization techniques
• Experience in constructing high-volume, low-latency data ingestion and transformation workflows
• Robust experience with Databricks, Delta Lake, Structured Streaming, and Spark Performance Tuning
• Skilled in managing TB to PB scale datasets, including partitioning strategies, file optimization, schema evolution, and data lifecycle management
• In-depth understanding of Data Lake, Lakehouse, and Modern Data Platform frameworks
• Practical experience in data modeling for analytical, operational, and reporting purposes
• Familiarity with implementing CI/CD pipelines using AWS CodePipeline, CodeBuild, CodeDeploy, GitHub Actions, or Jenkins
• Strong problem-solving abilities for production challenges, performance enhancements, and cost management
• Exceptional communication skills for client interaction, stakeholder engagement, and collaborative problem resolution

Technical Qualifications:

• Ensure the integrity, governance, security, monitoring, and support of data in production
• Work closely with architects, stakeholders, and cross-functional teams in Agile development settings
• Diagnose and enhance end-to-end AWS data platforms, streaming workflows, and cloud infrastructure

Desirable Skills:

Technology->Cloud->AWS, Technology->Cloud->AWS Core Services, Technology->Cloud->AWS - Database Solutions