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

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