Senior AWS Data Engineer: Data Lakes & Pipelines

Artifintech

Chicago (IL)

On-site

USD 120,000 - 160,000

Full time

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Job summary

Artifintech, a Chicago-based data solutions company, seeks an AWS Data Engineer to design, develop, and maintain scalable data pipelines and architectures in the AWS cloud. This role collaborates with data scientists, analysts and product teams to deliver robust data solutions, implement ETL/ELT processes, and optimize data lakes and data warehouses.

The ideal candidate has 5 years of experience on AWS data platforms, strong Python/SQL skills, and hands-on experience with services like Glue,

Qualifications

BS in Computer Science/Software Engineering/MIS or equivalent.
5+ years building data lakes/warehouses on AWS for large enterprises.
Strong Python, Shell, and SQL skills in data engineering context.
Hands-on with AWS services: Glue, S3, Athena, EMR Spark, RDS/Redshift, DynamoDB, Lambda, Step Functions, IAM, KMS, Secrets Manager.

Responsibilities

Design, build, and maintain scalable data pipelines and architectures on AWS.
Ingest data from on-premises to AWS and within AWS using Glue, S3, Redshift, Lambda, EMR Spark, Kinesis, and SQS.
Develop ETL/ELT processes to collect, process, and store data with quality, integrity, and security.
Architect end-to-end data solutions for data lakes and data warehouses on AWS.
Participate in architecture discussions for high-scale data projects.
Perform hands-on development, unit testing, and code reviews to ensure best practices.
Implement serverless apps using Lambda, API Gateway, Step Functions, and other AWS tech.
Migrate data from traditional databases, files, and APIs to AWS data lakes and Redshift.