AWS Data Engineer

Computer Task Group, Inc•Armonk, NY

1d•Onsite

About The Position

CTG is seeking an experienced AWS Data Engineer to design, develop, and optimize enterprise-scale data engineering solutions within the AWS Cloud ecosystem. The ideal candidate will have extensive experience building data lakes, data warehouses, batch and streaming data pipelines, and cloud-native ETL/ELT solutions using AWS services and modern open-source technologies.

Requirements

Strong AWS data engineering experience
Enterprise data lakes and data warehousing
End-to-end AWS data platform architecture
Batch and streaming data pipelines
ETL/ELT development and data modeling
Python, SQL, and shell scripting
Amazon S3
AWS Glue and Glue Catalog
Amazon EMR with Spark
Amazon Athena
Amazon Redshift and Redshift Spectrum
Amazon RDS
Amazon DynamoDB
AWS Lambda
AWS Step Functions
AWS IAM and KMS
AWS Database Migration Service (DMS)
API Gateway
Amazon SQS
Amazon Kinesis
Amazon OpenSearch (Elasticsearch)
Apache Kafka (MSK)
Apache Airflow
dbt
Spark (Python or Scala)
CI/CD and DevOps practices
Lakehouse architecture
Cloud analytics platforms
Performance tuning and optimization
Strong collaboration and communication skills

Responsibilities

Design, build, and maintain scalable AWS data engineering solutions.
Develop end-to-end data pipelines for ingestion, transformation, storage, and analytics.
Build batch and real-time data processing solutions using AWS Glue, EMR, Kinesis, Spark, and Kafka.
Design and implement enterprise data lakes and data warehouse architectures.
Develop ETL/ELT workflows using Python, SQL, Spark, and AWS-native services.
Migrate enterprise data from on-premises environments to AWS using AWS DMS.
Build API-driven data integration pipelines utilizing API Gateway, Lambda, and SQS.
Develop serverless data processing solutions using Lambda and Step Functions.
Design scalable data models supporting analytics and reporting initiatives.
Implement CI/CD pipelines and DevOps best practices for data engineering deployments.
Optimize performance, scalability, reliability, and cost across AWS data platforms.
Collaborate with architects, developers, analysts, and business stakeholders to deliver high-quality solutions.
Participate in code reviews, technical design discussions, and continuous improvement initiatives.