Data Engineer building solutions on AWS for high-performance data processing. Leading initiatives in data architecture and analytics for operational support.
Responsibilities
Design, develop, and maintain data pipelines using AWS Glue, AWS Lambda, Airflow, and complementary AWS services
Implement and optimize ETL/ELT processes for ingesting, transforming, and provisioning structured and unstructured data
Build distributed architectures using EC2, S3, IAM, CloudWatch, VPC, and other AWS components
Ensure data quality, integrity, and governance throughout the data lifecycle
Monitor systems, optimize performance, and reduce costs for data workloads
Collaborate with analytics, engineering, and product teams to advance data-driven solutions
Apply best practices for security, code versioning, and automation (CI/CD)
Requirements
Proven experience with AWS Glue (Jobs, Crawlers, Data Catalog)
Strong proficiency with Airflow for pipeline orchestration
Experience provisioning and operating EC2 instances
Advanced Python skills (including data manipulation libraries)
Experience with relational and non-relational databases (Redshift, RDS, DynamoDB, etc.)
Knowledge of S3, IAM, CloudWatch, SNS/SQS, and Lambda
Experience with Git and CI/CD tools
Familiarity with data modeling, Data Lake, and Data Warehouse concepts
Experience with Terraform or CloudFormation (preferred)
Knowledge of Redshift Spectrum, Athena, and Lake Formation (preferred)
Experience with big data environments (Spark, EMR, Databricks) (preferred)
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