Senior Data Engineer

Job Title : Sr. Data Engineer

Location : Phoenix, AZ

Job Type : Full Time

Compensation : $130,000 - $150,000 D.O.E.

Benefits : The position is eligible for medical, dental, vision, and life insurance coverage, & PTO

Senior Data Engineer

ROLE OVERVIEW

The Senior Data Engineer is responsible for designing, building, and maintaining scalable data platforms that support analytics, reporting, and advanced data-driven initiatives. This is a hands-on engineering role focused on developing reliable, high-performing data solutions while contributing to architectural standards, data quality, and governance practices.

The ideal candidate has strong experience with modern data architectures, data modeling, and pipeline development, and is comfortable collaborating across technical and business teams to deliver trusted, production-ready datasets.

KEY RESPONSIBILITIES

• Design and maintain data models across analytical and operational use cases to support reporting and advanced analytics.
• Build and manage data pipelines that ingest, transform, and deliver structured and unstructured data at scale.
• Contribute to data governance practices, including data quality controls, metadata management, lineage, and stewardship.
• Develop and maintain cloud-based data platforms, including data lakes, analytical stores, and curated datasets.
• Implement and optimize batch and near–real-time data ingestion and transformation processes.
• Support data migration and modernization efforts while ensuring accuracy, performance, and reliability.
• Partner with analytics, engineering, and business teams to understand data needs and deliver high-quality solutions.
• Enable reporting and visualization use cases by providing clean, well-structured datasets for downstream tools.
• Apply security, privacy, and compliance best practices throughout the data lifecycle.
• Establish standards for performance tuning, scalability, reliability, and maintainability of data solutions.
• Implement automation, testing, and deployment practices to improve data pipeline quality and consistency.

QUALIFICATIONS