Data Engineer

6d6 days ago

Wheels Up

Chamblee, US · Full-time · $140,667 – $150,000

About this role

At Wheels Up, we're a global leader in on-demand private aviation and strategic partner of Delta Air Lines. We commit to safe, reliable, enjoyable private air travel with a diverse fleet of owned aircraft and global charter network. Our mission delivers premium, personalized aviation experiences for every customer.

Join the growing Data Platform team as a versatile Data Engineer. Design, build, and operate scalable data pipelines powering analytics, reporting, and business insights. Combine hands-on data engineering with light DevOps in a modern cloud data platform for reliable, governed data solutions.

Develop reliable data ingestion, transformation, and orchestration workflows using PySpark and Spark SQL. Modernize the platform by migrating legacy SQL logic into distributed Spark-based pipelines. Support production operations through troubleshooting, monitoring, alerting, and performance tuning.

Collaborate cross-functionally with analytics, product, and engineering teams to deliver trusted data products. Manage Databricks workspace configuration, access controls, and permissions while contributing to standards on reliability, observability, cost optimization, and governance. Applications close 06/1/2026 at 12:00 PM ET.

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 performant, 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

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, 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