Data Engineer

Cantor Fitzgerald; Greater London; On-site; GBP 65,000 - 90,000; Full time

Job summary

Cantor Fitzgerald is seeking a Data Engineer in London to build and maintain data pipelines for AI and quant models. You will design scalable data architectures, ensure data quality, and create metadata systems to support model-ready datasets.

Collaborate with data scientists, manage time-series data, and implement data lineage and access controls, while staying current with best practices in modern cloud data stacks.

Qualifications

• Strong Python and SQL experience with production ETL/ELT pipelines.
• Proficient in cloud data stack technologies (Azure, Databricks, Delta Lake, Snowflake).
• Experience with time-series data and data quality monitoring.
• Bachelor's degree in CS/engineering or related field preferred; 2+ years of data engineering experience.

Responsibilities

• Build and maintain market, economic, research, news, and internal data pipelines, including Fenics/BGC data integration.
• Design and implement a scalable bronze/silver/gold data architecture to support AI and quant models.
• Establish and monitor data quality gates to ensure data integrity and accuracy.
• Develop and manage instrument, ticker, country, client, source, and theme metadata for effective data categorization and retrieval.
• Create APIs and tables for seamless integration with agent tools, dashboards, and quant models.
• Implement data lineage tracking, user entitlements, and permissions management systems.
• Monitor and optimize data pipelines for performance and efficiency, ensuring smooth data flow.
• Collaborate with data scientists and analysts to understand their data needs and provide model-ready datasets.
• Stay updated with trends in time-series and complex-data analysis, incorporating best practices into our data platform.
• Ensure data security and privacy compliance, adhering to industry standards and regulations.

Skills

Python

SQL

Time-series data

Cloud data stack

Data quality monitoring

kdb+ familiarity

Education

Bachelor's degree in Computer Science, Engineering, or related field

Tools

Azure

Databricks

Delta Lake

Snowflake

kdb+

Job description

As a Data Engineer, you will play a pivotal role in constructing the data foundation for our AI and quant model initiatives. Your responsibilities will encompass managing diverse data pipelines, from market and economic data to internal and news feeds. Additionally, you will be tasked with creating and maintaining a robust data architecture, ensuring data quality, and developing metadata systems. Your work will directly impact the performance and reliability of our client tools and quant models.

Responsibilities

• Build and maintain market, economic, research, news, and internal data pipelines, as well as Fenics/BGC data integration.
• Design and implement a scalable bronze/silver/gold data architecture to support our AI and quant models.
• Establish and monitor data quality gates to ensure data integrity and accuracy.
• Develop and manage instrument, ticker, country, client, source, and theme metadata for effective data categorization and retrieval.
• Create APIs and tables for seamless integration with agent tools, dashboards, and quant models.
• Implement data lineage tracking, user entitlements, and permissions management systems.
• Monitor and optimize data pipelines for performance and efficiency, ensuring smooth data flow.
• Collaborate with data scientists and analysts to understand their data needs and provide model-ready datasets.
• Stay updated with the latest trends in time-series and complex-data analysis, incorporating best practices into our data platform.
• Ensure data security and privacy compliance, adhering to industry standards and regulations.

Qualifications

• Strong proficiency in Python and SQL, with experience in production-level ETL/ELT processes.
• In-depth knowledge of cloud data stack technologies, such as Azure, Databricks, Delta Lake, or Snowflake.
• Experience with time-series data and complex data structures, demonstrating an understanding of data quality and monitoring.
• Ability to clean and transform messy data into structured, model-ready datasets, ensuring data integrity.
• Familiarity with ticker-level data processing, having worked with kdb+ or similar systems is an advantage.
• Excellent problem-solving and analytical skills, with a keen eye for detail and data accuracy.
• Strong communication and collaboration skills, able to work effectively with cross-functional teams.
• A proactive and self-motivated approach to work, with a passion for data engineering and continuous improvement.
• A bachelor's degree in Computer Science, Engineering, or a related field is preferred.
• 2+ years of relevant work experience in data engineering or a similar role.

Job Info

• Job Identification 248894
• Posting Date 08/19/2026, 09:06 AM
• Locations Five Churchill Place, London, Canary Wharf, E14 5HP, GB