AWS Data Engineer — Data Lakes & Pipelines Specialist

Machine Learning Technologies, LLC; Chicago (IL); On-site; USD 120,000 - 170,000; Full time

Job summary

Machine Learning Technologies, LLC in Chicago seeks an AWS Data Engineer to design, build, and maintain scalable data pipelines and architectures in AWS. You will work with data scientists, analysts, and business stakeholders.

The role focuses on ingestion, ETL/ELT, data lakes, and data warehouses, using Glue, Redshift, S3, Lambda, Kinesis, EMR, and related AWS services. You should have 5+ years in AWS data engineering for large enterprises, strong Python/SQL skills, and solid problem solving

Qualifications

• Bachelor's degree in CS/Software Engineering/MIS or equivalent.
• 5 years of AWS data lakes, data warehouses, and data apps experience.
• Strong Python, Shell, and SQL programming.
• Extensive AWS service experience: Glue, Redshift, S3, Lambda, EMR, Spark, Kinesis, SQS, etc.
• Experience with serverless data pipelines and CI/CD.
• Familiarity with data modeling and cloud architecture.
• Excellent communication and teamwork.

Responsibilities

• Design, build, and maintain data pipelines and architectures on AWS.
• Ingest data from on-prem to AWS and within AWS using Glue, Redshift, S3, Lambda, EMR, Spark, Kinesis, and SQS.
• Develop and manage ETL/ELT processes to collect, process, and store data.
• Architect end-to-end data solutions focusing on data lakes and data warehouses.
• Participate in architecture discussions for high-scale data projects.
• Perform hands-on development, unit testing, and code reviews.
• Implement serverless apps using Lambda, API Gateway, Step Functions.
• Migrate data from relational DBs, file systems, and APIs to AWS data lakes (S3, RDS, Aurora, Redshift).
• Implement high-velocity streaming with Kinesis, SQS, and Kafka if applicable.
• Define CI/CD strategies for enterprise data platforms.
• Collaborate with product, operations, QA, and cross-functional teams.
• Stay updated with new tech, run POCs, and onboard useful tools.
• Identify and resolve performance issues, optimize for cost, reliability, and scalability.

Skills

Python

SQL

Shell scripting

ETL/ELT

Data warehousing

Big data

Problem solving

Teamwork

Communication

Education

Bachelors degree in CS/SE/MIS

Tools

AWS Glue

Amazon Redshift

Amazon S3

AWS Lambda

Amazon EMR

Amazon Kinesis

SQS

RDS

Aurora

CloudFormation

IAM

KMS

Secrets Manager

Job description

Machine Learning Technologies, LLC in Chicago seeks an AWS Data Engineer to design, build, and maintain scalable data pipelines and architectures in AWS. You will work with data scientists, analysts, and business stakeholders.

The role focuses on ingestion, ETL/ELT, data lakes, and data warehouses, using Glue, Redshift, S3, Lambda, Kinesis, EMR, and related AWS services. You should have 5+ years in AWS data engineering for large enterprises, strong Python/SQL skills, and solid problem solving