Senior Data Engineer - Cloud Data Pipelines

Invesco EMEA; Atlanta (GA); Hybrid; USD 120,000 - 180,000; Full time

Benefits offered by this job

Flexible PTO

Hybrid work schedule

401(k) matching

Health & wellbeing benefits

Parental leave

Employee stock purchase plan

Job summary

Invesco is seeking an experienced Data Engineer to support advanced analytics and data integration for North America Client Transactions & Data. You will design, build, and manage large-scale batch and real-time data pipelines using AWS and modern data frameworks, collaborating with owners, analysts, and developers in an agile environment.

The role requires strong Python, SQL, and cloud skills, with a focus on data availability, quality, and scalable architectures.

Qualifications

• 5–7 years in data modeling, warehousing, and big data architectures.
• 0

Responsibilities

• Managing application and data integration platforms using AWS Cloud components.
• Building robust data pipelines using modern data engineering practices in a cloud architecture.
• Understanding the business and enabling development/reporting/integration life cycles per Agile standards.
• Ensuring data availability for business reporting and analytics within SLAs.
• Creating and managing data, applications and architecture documentation and artifacts.
• Maintaining code and environments to evolve data-driven analytics and understand customer behavior.

Skills

Data modelling

Data warehousing

Big data architectures

AWS data services

Airflow

Airbyte

SQL

DBT

Snowflake

Python

Linux scripting

Ansible

GitHub / Bitbucket

CI/CD

PostgreSQL

Aurora

Athena

Terraform

LLM prompt engineering

Education

BS in Computer Science, Applied Mathematics, Physics, Statistics or related data sciences field

Tools

Terraform

GitHub

Bitbucket

AWS

Job description

Invesco is seeking an experienced Data Engineer to support advanced analytics and data integration for North America Client Transactions & Data. You will design, build, and manage large-scale batch and real-time data pipelines using AWS and modern data frameworks, collaborating with owners, analysts, and developers in an agile environment.

The role requires strong Python, SQL, and cloud skills, with a focus on data availability, quality, and scalable architectures.