AWS Data Engineer

Vaspire Technologies Inc.; Juno Beach (FL); On-site; USD 90,000 - 130,000; Full time

Job summary

Vaspire Technologies Inc. is seeking an experienced data engineer to build and optimize production data pipelines in a cloud environment. You will leverage Python (including PySpark) for ETL and automation across large datasets, with a focus on AWS Glue jobs and DynamoDB data modeling.

Collaboration with API teams using Postman will be part of the role. You will work within the AWS stack (S3, Lambda, Step Functions, CloudWatch, IAM, KMS, Kinesis) and apply strong SQL and data warehousing

Qualifications

• Hands-on data engineering with production pipelines.
• Expert Python for data processing, ETL, and automation (PySpark).
• Proficient in AWS Glue, crawlers, and workflow orchestration.
• DynamoDB data modeling, capacity planning, streams and optimization.
• Solid understanding of AWS services: S3, Lambda, Step Functions, CloudWatch, IAM, KMS, Kinesis.
• Postman for API development, testing and collaboration.
• Strong SQL skills and data warehousing knowledge.
• Version control with Git; CI/CD and infrastructure as code (CloudFormation/Terraform).

Responsibilities

• Design and implement production data pipelines end-to-end.
• Develop and optimize AWS Glue jobs, crawlers and workflows.
• Model and optimize DynamoDB schemas and access patterns.
• Automate data workflows using AWS Step Functions and Lambda.
• Collaborate on API work with Postman for testing and docs.
• Maintain CI/CD pipelines and IaC configurations with CloudFormation/Terraform.

Skills

Hands-on data engineering

Python

ETL development

PySpark

SQL

Git

CI/CD

Infrastructure as Code

Tools

AWS Glue

DynamoDB

S3

Lambda

Step Functions

CloudWatch

IAM

KMS

Kinesis

Postman

Job description

Hands-on data engineering experience with proven track record of building production data pipelines

Expert-level proficiency in Python for data processing, ETL development, and automation (PySpark)

Deep experience with AWS Glue including job development, crawlers, triggers, and workflow orchestration

Strong expertise in DynamoDB data modeling, capacity planning, streams, and performance optimization

Solid understanding of AWS ecosystem: S3, Lambda, Step Functions, CloudWatch, IAM, KMS, Kinesis

Proficiency with Postman for API development, testing, and collaboration

Strong SQL skills and understanding of data warehousing principles

Experience with version control (Git), CI/CD tools, and infrastructure as code (CloudFormation/Terraform)