at UBS
Bulge Bracket Investment BanksPosted 7 days ago
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**Senior AI Engineer**: Develop, maintain, and enhance AI pipelines using Azure Databricks, Dagster, AKS, PySpark, and SparkSQL. Expertise in Kafka, REST APIs, and database platforms required. Lead data products to improve IT efficiency and developer experience. Experience managing data for 40,000+ employees.
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Full Job Description
| Are you passionate about data engineering? Are you keen to manage data that can materially help teams improve the way they work? You have the opportunity to join the team working on the new DevLens initiative, an ambitious data initiative to help our 40,000 IT employees organization accelerate value delivery to customers, improve organization efficiency and developer experience. Together with your team you will contribute to building and maintaining innovative data products spanning all engineering activities across UBS IT lines of business. You will work with large delta tables on Azure Databricks with Dagster, AKS, PySpark & SparkSQL, Confluent Kafka, REST APIs, database platforms, serving data products on Starburst/Trino data mesh. Were looking for a passionate Data Engineer to: Develop, support and improve data pipelines and data products with attention to governance including sourcing, lineage, modelling, security, quality, distribution and efficiency Automate testing & deployment where possible using CI/CD pipelines Build observability to monitor and resolve production issues Analyse and organize raw data and be able to combine multiple datasets of varying quality Take ownership and drive deliveries within a supportive team environment Follow engineering best practices, and ensure bank & regulatory compliance across the lifecycle Ensure the quality, security, reliability, and compliance of our solutions, promote re-use where possible. Help manage the department data inventory and data products Provide data support to internal & external stakeholders Be comfortable within a geographically spread, fast-moving Agile team Continuously up-skill, learn new technologies and practices, reuse strategic platforms and standards, evaluate options, and make decisions with long-term sustainability in mind. | Show more Data Engineer-Python, Pyspark, sql, Databricks |
