Data Engineer

Description

United's Digital Technology team is comprised of many talented individuals all working together with cutting-edge technology to build the best airline in the history of aviation. Our team designs, develops and maintains massively scaling technology solutions brought to life with innovative architectures, data analytics, and digital solutions.

Job Overview and Responsibilities

The objective of Data Engineer is to architect, implement and maintain robust data infrastructure that supports the end-to-end pipelines. This includes designing data ingestion processes, optimizing data storage solutions, and ensuring data quality and integrity. By building scalable and efficient systems, the Data Engineer empowers the team to access, preprocess, and analyze data effectively, ultimately facilitating the development and deployment of accurate and impactful data models.

• Design, build, and operate high-performance, cloud-native infrastructure and services that accelerate innovation across United
• Establish and maintain scalable containerized and serverless platforms, develop automation tools and applications using the AWS ecosystem, and proactively monitor, troubleshoot, and optimize critical data infrastructure
• Design and develop resilient batch and real-time data pipelines using Spark, Python, Databricks, and Flink
• Apply hands-on engineering expertise to deliver scalable, maintainable, and high-performing data solutions
• Support and optimize large-scale data pipelines within distributed, highly available, and horizontally scalable environments
• Remain current with advancements in cloud-native engineering and microservices architecture
• Evaluate, experiment with, and adopt emerging technologies that improve platform scalability, resilience, developer productivity
• Advance intelligent automation through modern AI technologies
• Collaborate effectively with cross-functional teams to translate business and technical requirements into practical solutions

Qualifications

What's needed to succeed (Minimum Qualifications):

• Bachelor's degree in Computer Science, Engineering, Mathematics, Statistics, or related field
• 2+ years experience in data engineering or related roles
• Proficiency in Python, SQL, data processing frameworks (Spark, pyspark)
• Familiar with AWS services such as Kinesis, Redshift, Glue, Athena, S3 etc.
• Ability to effectively collaborate with business users and product owners to design optimized data pipelines
• Must be legally authorized to work in the United States for any employer without sponsorship
• Successful completion of interview required to meet job qualification
• Reliable, punctual attendance is an essential function of the position

What will help you propel from the pack (Preferred Qualifications):

• Bachelor's degree in a field relevant to Machine Learning
• 3+ years experience in data engineering or related roles
• Advanced knowledge of ML algorithms and techniques
• Experience deploying machine learning pipelines into production
• Strong understanding of machine learning workflows, along with MLOPs tools and practices for managing ML workflows at scale