Enterprise Data Engineer & Architect w / AWS- REMOTE

Job Description

Enterprise Data Engineer & Architect with AWS - REMOTE

conversion to FTE after 6 months -

Location :  Remote (Must support CST hours, Stifel is based in St. Louis)

Duration :  3 months with a high likelihood of extension, and possibility of conversion to FTE

Overview :

Client is seeking a highly skilled Enterprise Data Architect to join our ongoing Enterprise Data Optimization (EDO) initiative. This project, which has been in development for two years, aims to enhance our data structuring capabilities and significantly improve data retrieval speeds across the organization. We are looking for a versatile, senior-level professional with a strong background in Enterprise data engineering and architecture to join our team. The breakdown of the work will be 50 / 50 between Engineering and Architecture.

Key Responsibilities :

• Collaborate with existing architects to split responsibilities equally between engineering and architecture.
• Engage in hands-on work, including coding in Python and SQL, to optimize data structures and API services.
• Develop and implement solutions to enable data retrieval speeds that are 10 times faster than current capabilities.
• Work closely with various teams to ensure seamless data access and integration across the organization.
• Provide thought leadership within the EDO space and act as a true consultant for best practices

Qualifications :

Requirements

Key Responsibilities : Collaborate with existing architects to split responsibilities equally between engineering and architecture. Engage in hands-on work, including coding in Python and SQL, to optimize data structures and API services. Develop and implement solutions to enable data retrieval speeds that are 10 times faster than current capabilities. Work closely with various teams to ensure seamless data access and integration across the organization. Provide thought leadership within the EDO space and act as a true consultant for best practices Qualifications : Minimum of 10+ years of experience in Data Engineering / Architecture. Proven expertise as a “jack of all trades” in Enterprise Data Engineering. Proficiency in AWS, Terraform, Kubernetes, Python, and SQL. Experience in implementing and automating Kubernetes, with the ability to build Kubernetes environments independently without using Glue. Extensive experience with AWS services, including S3, Redshift, Aurora Postgres, Glue, Lambda, Step Functions, Lake Formation, and Kinesis. Strong background in AWS with Terraform, particularly in automating infrastructure delivery. Experience with CI / CD processes using Azure DevOps (ADO) and GitHub. Strong knowledge of Python and Postgres SQL. Some experience with MCP servers is a plus. Preferred Experience : A background in finance is advantageous but not required.