Senior Data Engineer

Intercontinental Exchange Holdings; Atlanta (GA); On-site; USD 140,000 - 170,000; Full time

Job summary

Intercontinental Exchange Holdings is seeking a Senior Data Engineer to lead design and implementation of our next-generation data platform in Atlanta, GA. You will build on-premises data pipelines with governance and data quality, collaborating with stakeholders to enable ML and AI workflows.

You will mentor engineers, implement CI/CD for data pipelines, and partner with ML teams to create scalable feature pipelines for batch and real-time processing. 5+ years in data engineering required.

Qualifications

• Bachelor's degree in CS, CE, data science, mathematics, or related fields.
• 5+ years in data engineering with at least 2 years on enterprise-scale platforms.
• Strong SQL and Python for data transformation and pipeline development.

Responsibilities

• Design, build, and maintain on-premises data orchestration platform using best-in-breed open source tools.
• Create self-service capabilities for teams to build data pipelines with minimal engineering support.
• Implement robust data quality testing frameworks to ensure data integrity across the lifecycle.
• Establish data engineering best practices, including version control, CI/CD for data pipelines, and automated testing.
• Collaborate with ML/AI teams to build scalable feature engineering pipelines for batch and real-time processing.
• Mentor junior engineers and advocate for engineering excellence in data practices.

Skills

SQL

Python

Data pipelines

Data governance

CI/CD

Kubernetes

Education

Bachelor's degree in CS/CE/Data Science

Tools

Airflow

Kubernetes

Docker

Job description

Locations: Atlanta, Georgia

Req ID: 13654

Job Purpose

We're seeking a talented Senior Data Engineer to join our Enterprise Architecture team in a cross-cutting role that will help define and implement our next-generation data platform. In this pivotal position, you'll lead the design and implementation of scalable, self-service data pipelines with a strong emphasis on data quality and governance. This is an opportunity to shape our data engineering practice from the ground up, working directly with key stakeholders to build mission-critical ML and AI data workflows.

Responsibilities

• Design, build, and maintain our on-premises data orchestration platform using the best-in-breed open source tools
• Create self-service capabilities that empower teams across the organization to build and deploy data pipelines without extensive engineering support
• Implement robust data quality testing frameworks that ensure data integrity throughout the entire data lifecycle
• Establish data engineering best practices, including version control, CI/CD for data pipelines, and automated testing
• Collaborate with ML/AI teams to build scalable feature engineering pipelines that support both batch and real-time data processing
• Develop reusable patterns for common data integration scenarios that can be leveraged across the organization
• Work closely with infrastructure teams to optimize our Kubernetes-based data platform for performance and reliability
• Mentor junior engineers and advocate for engineering excellence in data practices

Knowledge and Experience

• At least a Bachelor’s degree in Computer Science, Computer Engineering, Data Science, Mathematics, Engineering, or related disciplines.
• 5+ years of professional experience in data engineering, with at least 2 years working on enterprise-scale data platforms
• Deep expertise with orchestrating workflows, performance optimization, and operational management
• Strong understanding of data transformation techniques, including experience with testing frameworks and deployment strategies
• Experience with stream processing frameworks and technologies
• Proficiency with SQL and Python for data transformation and pipeline development
• Familiarity with containerized application deployment
• Experience implementing data quality frameworks and automated testing for data pipelines
• Ability to work cross-functionally with data scientists, ML engineers, and business stakeholders

Preferred Qualifications

• Experience with self-hosted data orchestration platforms (rather than managed services)
• Background in implementing data contracts or schema governance
• Knowledge of ML/AI data pipeline requirements and feature engineering
• Experience with real-time data processing and streaming architectures
• Familiarity with data modeling and warehouse design principles
• Prior experience in a technical leadership role

Intercontinental Exchange, Inc. is an Equal Opportunity Employer. All qualified applicants will receive consideration for employment without regard to legally protected characteristics.