Top Fintech Data Engineering Jobs

Own end-to-end data and analytics for SaaS clients: collect requirements, stand up data infrastructure, migrate reporting to Valon Data Schema, build dbt pipelines, rewrite SQL queries and dashboards, conduct analyses, and support client operations under tight deadlines.

As a Senior Machine Learning Engineer, you'll build and deploy ML models for risk and fraud detection, leading technical efforts and collaborating cross-functionally.

Role involves executing trading strategies, developing quantitative models, and optimizing trading systems within a collaborative team environment.

Participate in a 5-day immersive program focusing on trading systems development using C++ and Python, mentored by software developers.

Design, build, and execute data pipelines and migration strategies to move legacy data into Temenos systems. Perform data mapping, cleansing, testing, validation, and post-migration support. Collaborate with stakeholders, QA, and vendors, use Temenos migration and ETL tools, and document transformation logic while ensuring data integrity and minimal cutover downtime.

As a Senior Data Engineer, you will design, build, and maintain scalable data platforms, ETL pipelines, and support analytics and ML workflows, ensuring data quality and cross-functional collaboration.

The Quantitative Researcher will develop and manage trading algorithms, optimize strategies, and collaborate with traders while supporting junior team members.

As a Senior Data Engineer, you will architect and implement cloud-native data solutions, optimize pipelines, and collaborate across teams to improve data reliability and scalability.

The intern assists with research projects in fixed income and equities, maintains quant infrastructure, and supports model construction while building macroeconomic factor databases.

The Data Engineer will enhance data pipelines, support data analysts, and optimize data architecture for cross-functional teams. This role involves data extraction, transformation, and analytics to meet reporting needs.