Data Engineer

Wheels Up • Chamblee, GA

23h • Hybrid

About The Position

Wheels Up is looking for a versatile Data Engineer to join our growing Data Platform team. In this role, you will design, build, and operate scalable data pipelines that power analytics, reporting, and business insights. You’ll combine hands‑on data engineering with light DevOps and operational responsibilities, working within a modern cloud data platform to deliver scalable, reliable, and governed data solutions that power analytics and business insights.

Requirements

• Bachelor’s (with 4+ years relevant experience) OR Master’s (with 2+ years relevant experience).
• 3+ years of hands‑on experience in data engineering, building and supporting production data pipelines
• Strong proficiency in Python and SQL, with experience writing performance, maintainable code
• Hands‑on experience with distributed data processing frameworks, such as Apache Spark (PySpark, Spark SQL)
• Solid understanding of ETL/ELT design patterns, data modeling, cost optimization, and performance optimization
• Experience working in cloud environments (Azure preferred; AWS or GCP acceptable)
• Familiarity with data lake or lakehouse architecture and modern analytics platforms
• Experience supporting production data systems, including troubleshooting, monitoring, and operational support
• Strong communication skills with the ability to collaborate effectively across technical and non‑technical teams
• High attention to detail, strong data intuition, and a commitment to data quality and reliability
• Comfortable working in a fast‑paced environment with evolving requirements and priorities

Nice To Haves

• Experience with Databricks and orchestration tools (Workflows, Terraform)
• DevOps familiarity (CI/CD, GitHub Actions, Azure DevOps)
• Databricks, Azure, or cloud certifications a plus
• Python, SQL, Spark,
• Hands on Experience with at least (1) Cloud service, we use Azure here at Wheels Up
• Advanced level skills
• Data Engineer Falin Python
• Data Manipulation
• Computer Science or Engineering Background

Responsibilities

• Design, build, and maintain scalable, cloud‑native data pipelines using PySpark and Spark SQL
• Develop reliable data ingestion, transformation, and orchestration workflows to support analytics and reporting needs
• Modernize the data platform by migrating legacy SQL logic and stored procedures into distributed, Spark‑based pipelines
• Develop automation and tooling for CI/CD automation, monitoring, alerting, and data quality checks across the data platform
• Support production data operations, including troubleshooting pipeline failures, resolving bugs, and tuning performance
• Manage Databricks operational responsibilities, including workspace configuration, access controls, and permissions
• Collaborate cross-functionally, partnering with analytics, product, and engineering teams to deliver trusted, well‑governed data products
• Contribute to platform standards and best practices around reliability, observability, cost optimization, and data governance

Benefits

• Tuition Reimbursement
• Competitive 401(k)
• Comprehensive Medical, Dental, and Vision Insurance
• Complimentary access to mental health and wellness counseling through Spring Health
• Financial planning assistance
• A variety of additional programs and services in support of your total well-being

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level
• Number of Employees: 501-1,000 employees