Research - Data Engineer

Your role

Do you have sharp data Analytic/Engineering skills? Do you know how to solve problems and develop innovative solutions? Do you enjoy responsibility and independent work? We’re looking for Data Engineer with practical knowledge in designing, building, deploying and maintaining scalable systems.
• able to develop highly scalable data processing pipelines,
• able to develop data query and analysis services to be leveraged by clients, internally and externally
• maintain a high standard of code quality within the broader engineering team
• adapt the latest data processing and infrastructure techniques to our growing stack
• well organized and dependable,
• able to turn large datasets into an asset across the organization,
• able to collect and combine data from multiple sources,
• analyze it for insights and produce great visuals

Your team

UBS Evidence Lab is looking for a software engineer to join its Engineering Team. The team's focus is building scalable frameworks and services used to analyze large datasets in the context of financial analysis. They leverage well-established engineering processes and techniques pioneered by giants in the tech industry. Projects span general pipelining to building internal web tools to helping develop low-latency query and analysis engines.
No background in finance is required, so this is a great opportunity to get exposure to the finance industry. Think of the team as a well-funded engineering startup within an investment bank.

Your expertise

Minimum Qualifications:
• 3 to 7 years of work experience as Data engineer
•established track record in designing, building, deploying, and maintaining scalable systems
• Second-nature knowledge of algorithms and data structures
• Knowledge developing and debugging Python, SQL
Preferred Qualifications:
• Formal education in Computer Science or related quantitative field
• Experience with distributed systems
• Experience with Hadoop or Spark or Apache