Senior Data Engineer - Cloud-Native Trading Platform

Invesco; Atlanta (GA); Hybrid; USD 140,000 - 190,000; Full time

Benefits offered by this job

Hybrid work schedule

401(K) matching

Health & wellbeing benefits

Parental Leave benefits

Employee stock purchase plan

Job summary

Invesco’s Investment Technology team is seeking a Senior Engineer to join the Systematic Trading Technology group. You will design and deliver scalable, cloud-native trading platforms and partner with Traders, Quants, and Business Analysts to enable better investment decisions.

You will lead hands-on development, contribute to SDLC pipelines, and help advance AI-driven capabilities in production systems while aligning with security and enterprise architecture standards.

Qualifications

• Experience building data analytics solutions for investment management or trading.
• Proficiency with Snowflake, SQL Server/Oracle, and Python in data/ETL contexts.
• Knowledge of cloud AWS and BI tools (Power BI/Tableau) a plus.
• Familiarity with CRD/Portware and investments is advantageous.
• Ability to communicate complex technical concepts to non-technical stakeholders.

Responsibilities

• Collaborate with Traders, Quants, and Analysts to build scalable trading platforms.
• Develop cloud-native solutions and optimize trading workflows for the global desk.
• Lead SDLC activities: code reviews, testing, and pipeline automation.
• Drive AI-driven capabilities, analytics, and automation within production systems.
• Coordinate with Enterprise Architecture, Security, and Infrastructure teams.

Skills

Snowflake

MS SQL Server

Oracle

Python

AWS

Power BI

Tableau

Portware

Investments

Cloud-native

Job description

Invesco’s Investment Technology team is seeking a Senior Engineer to join the Systematic Trading Technology group. You will design and deliver scalable, cloud-native trading platforms and partner with Traders, Quants, and Business Analysts to enable better investment decisions.

You will lead hands-on development, contribute to SDLC pipelines, and help advance AI-driven capabilities in production systems while aligning with security and enterprise architecture standards.