AWS Data Engineer

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

US Citizen, Green Card, H-1B, OPT-EAD, CPT, Other

We are seeking a talented AWS Data Engineer to join our dynamic Data Engineering team The ideal candidate will be responsible for designing developing and maintaining scalable data pipelines and architectures in the AWS cloud environment This role will collaborate closely with data scientists analysts and other business stakeholders to deliver robust data solutions

Key Responsibilities:

• Design build and maintain efficient reusable and reliable architecture and code for data pipelines and data applications on AWS
• Build robust data ingestion pipelines from onprem to AWS and within AWS using AWS services such as Glue Redshift S3 Lambda EMRSpark Kinesis and SQS
• Develop and manage ETLELT processes to collect process and store data from multiple sources ensuring data quality integrity and security
• Architect and implement endtoend data solutions ingestion storage integration processing access on AWS with a focus on data lakes and data warehouses
• Participate in the architecture and system design discussions for highscale data engineering projects
• Independently perform handson development unit testing and participate in code reviews to ensure adherence to best practices
• Implement serverless applications using AWS Lambda API Gateway Step Functions and other AWS technologies
• Migrate data from traditional relational databases file systems and APIs to AWSbased data lakes S3 RDS Aurora and Redshift
• Implement highvelocity streaming solutions using Amazon Kinesis SQS and Kafka preferred
• Architect and implement CICD strategies for enterprise data platforms
• Collaborate with product operations QA and crossfunctional teams throughout the software development cycle
• Stay abreast of new technology developments implement POCs for new toolstechnologies and onboard them for realworld use cases
• Identify and resolve performance issues and continuously optimize for cost reliability and scalability

Required Qualifications:

• Bachelors degree in Computer Science Software Engineering MIS or equivalent combination of education and experience
• 5 years of experience implementing and supporting data lakes data warehouses and data applications on AWS for large enterprises
• Strong programming experience with Python Shell scripting and SQL
• Solid experience with AWS services CloudFormation S3 Athena Glue EMRSpark RDS Redshift DynamoDB Lambda Step Functions IAM KMS Secrets Manager
• Experience in serverless application development and data pipeline orchestration
• Experience in system analysis design development and implementation of data ingestion pipelines in AWS
• Knowledge of ETLELT data modeling and big data technologies
• Familiarity with data warehousing concepts and cloudbased architecture
• Strong problemsolving skills and attention to detail
• Excellent communication and teamwork abilities

Preferred Qualifications:

• Experience with additional AWS services API Gateway ElasticSearch SQS
• Experience with infrastructureascode tools eg Terraform CloudFormation
• Experience with DevOps practices and CICD pipelines
• Experience implementing endtoend streaming solutions Amazon Kinesis SQS Kafka
• AWS Solutions Architect or AWS Developer Certification preferred
• Understanding of Lakehousedata cloud architecture
• Knowledge of data governance and compliance standards

We are an equal opportunity employer. All aspects of employment including the decision to hire, promote, discipline, or discharge, will be based on merit, competence, performance, and business needs. We do not discriminate on the basis of race, color, religion, marital status, age, national origin, ancestry, physical or mental disability, medical condition, pregnancy, genetic information, gender, sexual orientation, gender identity or expression, national origin, citizenship/ immigration status, veteran status, or any other status protected under federal, state, or local law.