Data Engineer

Responsibilities

• Develop, support, and improve data pipelines and data products with a focus on governance, lineage, modeling, and security
• Build and maintain innovative data products using Azure Databricks, PySpark, and SparkSQL
• Automate testing and deployment processes using CI/CD pipelines
• Implement observability to monitor and resolve production issues
• Analyze and organize raw data from multiple datasets of varying quality
• Ensure the quality, security, reliability, and compliance of all solutions in accordance with banking regulations
• Collaborate within a geographically distributed Agile team to drive deliveries

Requirements

• 8+ years of experience in data engineering with large-scale data solutions
• Proficiency in Azure Databricks and open table formats such as Delta Table or Iceberg
• Strong coding expertise in Python and SQL, specifically for developing Spark solutions
• Solid understanding of data streaming and batch ingestion (Kafka, CDC, SCD types)
• Experience with workflow orchestration tools such as Dagster or Airflow
• Proficiency in engineering best practices including CI/CD, Automated Testing, Git, and observability
• Bachelor's degree or equivalent relevant experience

Preferred Qualifications

• Experience with containerization technologies like Docker or Kubernetes
• Experience with Infrastructure as Code (Terraform)
• Knowledge of serving data products on Starburst/Trino data mesh

About the Company

UBS is a leading global wealth manager and the leading universal bank in Switzerland, providing diversified asset management solutions and focused investment banking capabilities. We value diversity, collaboration, and engineering excellence.