Data Engineer- W2 Candiates Only

Must Have Skills: AWS Glue, Lambda, Redshift, EMR

Detailed Job Description

• Architect and implement cloud native data pipelines on AWS.
• Build serverless compute layers using Lambda, Step Functions, and Airflow.
• Design data lake storage strategies using S3, Glue, Athena, and Redshift.
• Integrate real-time data streams via Kinesis and SQS
• Collaborate with business analysts to translate reporting requirements into schema and pipeline design
• Own data quality, pipeline monitoring, and alerting via CloudWatch
• Lead schema design for Athena and Postgres tables DDL, partitioning, indexing
• Evaluate and integrate AI/ML services Bedrock, Comprehend, Transcribe
• Document architecture decisions and maintain runbooks
• 5 years AWS data engineering experience Expert Python data transformation, boto3, async processing Deep knowledge of S3, Lambda, SQS, Kinesis, Step Functions, EventBridge, DynamoDB, Glue, Athena, Redshift, Airflow
• Airflow production DAG development and debugging SQL complex queries, window functions, partitioning, performance tuning IAM roles, policies, cross account access, permissions boundaries

Top 3 responsibilities you would expect the Subcon to shoulder and execute
Architect and implement cloudnative data pipelines on AWS
Build serverless compute layers using Lambda, Step Functions, and Airflow
Design data lake storage strategies using S3, Glue, Athena, and Redshift

Nice to have skills: SQL, Python/Pyspark, DAG

Minimum years of experience: 5-8 years