Lead Cloud Data Engineer - AWS Glue, Redshift & PySpark

Raymond James; Southfield (MI); Hybrid; USD 130,000 - 190,000; Full time

Benefits offered by this job

Medical, dental, and vision

Disability insurance

Retirement savings

Paid time off

Job summary

Raymond James is seeking a Lead Cloud Data Engineer to design and optimize data pipelines using AWS Glue, PySpark and Redshift. This hybrid role requires in-office presence 2-3 days per week in Southfield, MI, with collaboration across data science, analytics, and IT teams.

The ideal candidate will drive data quality, governance, and scalable solutions, mentoring junior engineers and evolving best practices for cloud-based analytics platforms.

Qualifications

• Bachelor’s degree in computer science or related field is required.
• 6–10 years general work experience in data engineering or similar roles.
• Strong experience with AWS data services and cloud architectures.

Responsibilities

• Design and develop scalable ETL pipelines using AWS Glue and PySpark.
• Integrate data from multiple sources into Amazon Redshift with quality controls.
• Optimize performance of data processing jobs and Redshift queries.
• Implement IaC with Terraform and monitor pipelines for reliability.
• Collaborate with data scientists and analysts to understand data needs.
• Mentor junior engineers and document data workflows and standards.

Skills

AWS cloud services

PySpark

Python

Data warehousing

ETL pipelines

Analytics concepts

Networking/infrastructure

Documentation & coding standards

Performance tuning

Cloud security basics

DB platforms & ETL architectures

Education

Bachelor's degree in Computer Science or related

Tools

Terraform

Airflow

Kafka

SageMaker

Amazon Redshift

Job description

Raymond James is seeking a Lead Cloud Data Engineer to design and optimize data pipelines using AWS Glue, PySpark and Redshift. This hybrid role requires in-office presence 2-3 days per week in Southfield, MI, with collaboration across data science, analytics, and IT teams.

The ideal candidate will drive data quality, governance, and scalable solutions, mentoring junior engineers and evolving best practices for cloud-based analytics platforms.