Data Engineer

Description

We are looking for a Data Engineer to help strengthen enterprise data capabilities and expand access to reliable information across the organization. This position focuses on building scalable data solutions that support analytics, reporting, and informed decision-making. Based in San Diego, California, the role works closely with both technical and business stakeholders to deliver dependable, high-quality data assets.

Responsibilities:
Build and maintain robust data pipelines that move and transform information from diverse platforms into usable analytical datasets.
Develop and support end-to-end integration workflows across multiple systems to ensure consistent and timely data delivery.
Design data models and reporting structures that improve usability, performance, and accessibility for downstream analytics needs.
Track data quality and platform performance, investigating issues and resolving reliability concerns before they affect business operations.
Collaborate with cross-functional partners to translate reporting and analytics needs into scalable technical solutions.
Maintain clear documentation and contribute to governance practices that promote accuracy, consistency, and operational discipline.
Assist with validation, release activities, and continuous enhancements to improve the overall effectiveness of the data platform.
Contribute to cloud-based data engineering efforts using tools such as Azure Data Factory, Azure Data Lake, Microsoft Fabric, Spark, Kafka, and Hadoop where appropriate.

Requirements

At least 5 years of hands-on experience in data engineering, data integration, or a closely related technical discipline.
Strong background working with cloud data ecosystems and modern integration frameworks in production environments.
Advanced SQL expertise, including query optimization, troubleshooting, and performance improvement.
Proven experience creating and supporting production ETL or ELT pipelines across multiple data sources.
Solid understanding of dimensional modeling and the design of analytics-focused datasets.
Hands-on experience with Python, Apache Spark, or similar technologies used for large-scale data processing.
Ability to communicate clearly, solve complex technical problems, and work effectively with both business and engineering teams.
A bachelor's degree in computer science, information systems, or a related field is preferred; relevant cloud or data certifications are a plus.

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