Credit Principal Algo Data Lead

UBS
London, UK
16 days ago

Role details

Contract type
Permanent contract
Employment type
Full-time (> 32 hours)
Experience level
Expert
Experience required
2 years minimum
Working hours
Regular working hours
Job source

Tech stack

Java (Programming Language) Artificial Intelligence Airflow Data Analysis Microsoft Azure Continuous Integration Data Infrastructure Extract Transform Load (ETL) Relational Databases PostgreSQL Log Analysis Online Transaction Processing
+14 more
Operational Databases Query Optimization Power BI Data Processing ReactJS Grafana Apache Spark Indexer Data Analytics Data Management Streamlit Framework Terraform Data Pipelines Docker

Job description

  • Are you excited by the prospect of engineering solutions in Credit Principal Algo Trading team ? Are you passionate about building and delivering AI solutions?
  • We are seeking a talented and self-driven candidate to join and lead our Credit Principal Algo Credit Algo Data team within UBS Global Markets
  • This is a fast paced and collaborative team that are responsible for the development and enhancement of our growing trading analytics platform

We’re looking for a Credit Principal Algo Data lead to:

  • Participate in the design, development, of our data platform
  • Play a key role in designing and implementing the next generation of platform, partnering closely with Algo Quant Trading, Trading, and Sales from idea generation through to production launch
  • Build and maintain strong working relationships with Algo Quant Trading, Trading, Quant, Sales, IT, and Risk partners in London and across regions

Requirements

  • 8+ years of hands-on data engineering in production environments, with strong, idiomatic Python used for reliable, well-tested systems (not exploratory notebooks).
  • Design and operation of large-scale ETL/ELT pipelines, including orchestration (Airflow, Prefect, or similar) and reliability patterns such as retries, backfills, and exactly-once semantics.
  • Deep experience with Azure, including AKS, Helm, EventHub, observability tools (e.g. Log Analytics) and infrastructure-as-code (e.g. Terraform).
  • Advanced experience operating Delta tables at scale, covering transaction semantics, schema evolution, partitioning, and compaction, alongside highly optimised analytical query execution using DuckDB or Apache Spark.
  • Production-grade relational database expertise, particularly PostgreSQL (query tuning, indexing, partitioning, replication, and schema design across OLTP and analytics).
  • Strong KDB experience, covering key concepts such as tp/ctp/rdb/hdb and differences between real-time vs historical queries and usage of gateways.
  • Containerised data workloads using Docker and Kubernetes, with reproducible, environment-agnostic deployment of data infrastructure.
  • Analytical data modelling expertise, including dimensional models or data vaults, schema evolution, slowly changing dimensions, and downstream impact analysis.
  • Strong experience managing and troubleshooting environments based on visualization and data analytics technologies such as JupyterHub, PowerBI, Streamlit and Marimo.
  • Batch and streaming processing proficiency, including late data handling, watermarking, backfills, and explicit throughput vs. latency trade-offs.
  • Production data reliability and observability mindset, covering lineage, data quality checks, SLAs, CI/CD for data pipelines, and close collaboration with quants, risk managers, and traders to deliver trustworthy data products.
  • 2+ years of experience in Java, covering react-based applications.
  • Experience delivering business facing solutions enhanced by AI and using AI assisted development (including prompt driven workflows and MCP servers) to reduce context switching and accelerate reliable delivery.
  • You’re curious to explore how AI can improve how we build, deliver, and optimize workflows. You do this with sound judgment - validating outputs and aligning with policies, risk standards, and ethical use.

*LI-GB

Benefits & conditions

We’re committed to disability inclusion and if you need reasonable accommodation/adjustments throughout our recruitment process, you can always contact us.

Disclaimer / Policy statements

UBS is an Equal Opportunity Employer. We respect and seek to empower each individual and support the diverse cultures, perspectives, skills and experiences within our workforce.

Your team

  • A highly technical and innovative team leading automated trading in eCredit
  • Focused on maximising automation and performance in order to drive eTrading revenues
  • Operating in a highly agile manner, releasing to production multiple times per day
  • The team is known for being collaborative and diverse, with a mandate to deliver meaningful change

About the company

At UBS, we know that it’s our people, with their diverse skills, experiences and backgrounds, who drive our ongoing success. We’re dedicated to our craft and passionate about putting our people first, with new challenges, a supportive team, opportunities to grow and flexible working options when possible. Our inclusive culture brings out the best in our employees, wherever they are on their career journey. And we use artificial intelligence (AI) to work smarter and more efficiently. We also recognize that great work is never done alone. That’s why collaboration is at the heart of everything we do. Because together, we’re more than ourselves.

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